THE EFFECTS OF marxtumfioa ON AGRICULTURAL LAND USP. IN LOWER W Thesis for 1+» Dogm cf Ph. D. MECHKGAX STA?! UNIVERSETX’ Charms. W. .‘ansen 1958 O~169 This is to certify that the thesis entitled THE EFTEXJTS OF URBANIZATION ON AGRICULTURAL IAND USE IN IOWER MICHIGAN presented by Clarence W. Jensen has been accepted towards fulfillment of the requirements for PhoDo degree in AgI‘iCUltU :11 Economics Majo professor Date-W ,9) I75? @4 M LIBRARY Michigan Sum University THE EFFECTS OF URBANIZATION ON AGRICULTURAL LAND USE IN LOWER MICHIGAN BY Clarence W. Jensen AN ABSTRACT Submitted to the School for Advanced Graduate Studies of Michigan State University of Agriculture and Applied Science in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Agricultural Economics 1958 Approved «4% 6M ' T Clarence W. Jensen -1- Agriculture in Lower Michigan, as elsewhere, has been releasing a great many acres of land to urban and other non-agricultural uses of land at varying rates since urban areas first began developing. The most recent upsurge in the outward expansion of the urban population began during the war-time years of the 1940's. During this period, the state of Michigan experienced a large influx of migrants to its war, and other, industries. Fringe area studies completed during the last ten to fifteen years have noted the trend of urban people toward the suburbs and rural area residences. Such movements have brought many problems to a large number of areas, many of which were ill-equipped to handle them. This treatise has attempted to indicate what some of the effects of such pOpulation movements might be upon the agricultural sector of the economy. The area of study is limited to the lower 38 counties in the state of Michigan. It is here that the majority of the urbaniz- ing of large land areas has taken place, and here that the effects of urbanization would be most strongly felt. An inventory of land uses in the study area discloses a very sub- stantial acreage of land that has moved into urban and urban-related uses. Since 1940, urban and related land acreages in the major city areas of the study area have increased by more than 385,000 acres. Urban land acres amount to slightly more than one-half of the total in non-agricultural uses of land. Clarence W. Jensen -2- Other land uses, public in nature, are becoming increasingly important in the acreages required to meet the needs of an expanding urban population. Such land uses as highways and roads, parks, recrea- tion areas, and Metropolitan Authority parks are expanding rapidly as the population becomes more demanding of services for transporta- tion and recreation facilities. When townships are arrayed in concentric rings around the central cities, the effect of urbanization upon agriculture is quite evident. Farms nearer the city are fewer and smaller, and generally have a larger proportion of their crOpland left idle. Statistical regression tests relating rural non-farm population to the pattern of land use by county also indicate non-farm population effects upon farms in the area. When counties are arrayed according to their percentage of rural non-farm population, considerable impact upon agricultural land use is noted. Especially significant is the large increase in extremely small farms, in the number of part-time farms, and in the amount of farmland that is rented out as the rural non-farm papulation percentage increases. No effect of urbanization was noted upon the intensity of grazing, where the measure of this was the per cent of the total farm pastured, and animal units per acre of pasture. Neither was there any signifi- cance in the relationship between rural non-farm population and the proportion of cropland devoted to grain crops, hay and legumes, or other crops. THE EFFECTS OF URBANIZATION ON AGRICULTURAL LAND USE IN LOWER MICHIGAN By Clarence W. Jensen A THESIS Submitted to the School for Advanced Graduate Studies of Michigan State University of Agriculture and Applied Science in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Agricultural Economics 1958 '7 r) I A Approved / /\ ('1, (t‘ 14' L /§dr"( 01..‘(~ \ U ACKNOWLEDGEMENTS The author is indebted to Dr. Raleigh Barlowe, chairman of the guidance committee, for his counsel and guidance during the develop- ment and completion of this thesis, and to Dr's. V. E. Smith and L. W. litt who helped plan the author's graduate program and re- viewed the manuscript. Also appreciated are the suggestions and encouragement received from other staff members at Michigan State University and by colleagues at Montana State College. Thanks are also due a wife and family whose patience was often tried, to Mr. Charlie Liu, graduate student at Montana State College, who assisted with some of the tabulations, and to Mrs. Catherine Lowis for her time and effort in typing the manuscript. Any errors and ommissions are the responsibility of the author. 1921 1939 1940-1946 1951 1952 1952-1955 1955 BIOGRAPHICAL Clarence w. Jensen Candidate for the degree of Doctor of PhilosOphy Born at McCabe, Montana Graduate Culbertson High School Culbertson, Montana United States Army 8.8., Montana State College M.S., Montana State College Graduate Study, Michigan State University Assistant Professor of Agricultural Economics and Economics, Montana State College II III IV VI TABLE OF CONTENTS INIRQDLUIIme O O O O O O O O 0 O O O O 0 Objectives of study The 8tUdy area. e e e e e e e e e e e e e Sources Of d‘t. e e e e e e e e e e e e e Methodology . . . . . . . . . . . . . . . REVIEW OF LITERATURE. e e e e e e e e e e Economic studies. . . . . . . . . . . . . SOCiOIOgY e e e e e e e e e e e e e e e e Geogr'Phy e e e e e e e e e e e e e e e e Political Science . . . . . . . . . . . . 'URBANIZATION AND ITS EFFECTS IN THE RURAL Urbanization and the ripening principle . Effects upon agricultural land use. . . . The supply of agricultural land . . . . . C O ' O O O O O O O O O O AREAS URBAN AND RELATED LAND USES IN SELECTED CITY AREAS. Growth observed in selected city areas. Township changes in tiers around cities Flint e e e e e e e e e e e e e e e e e LCDSIHQ e e e e e e e e e e e e e e e e ”to Pleasant. e e e e e e e e e e e e e All mapped city areas . . . . . . . . . Rural non-farm population adjustments . Estimated rural non-farm.land holdings. Urban acreage potentials. . . . . . . . AGRICULTURAL CHANGES IN THE STUDY AREA. . The townships . . . . . . . . . . . . . . Th. Count1CO e e e e e e e e e e e e e e Per cent rural non farms the independent SUMMARY AND CONCLUSIONS . e . . e . e e . Sunnlry e e e a e e e e e e e e e e e e e CODC1U51°HO e e e e e e Urban .Xp‘fl‘ion e e e e e e e e e e e e a variable. 0 Page s..- uesoo 0o . .0 0 m , . 3.30 0003 .00: mo on>H can >ucsoo >n .moh< >u=wm :3 000: 6:03 summucoz mo momaouo< 0 030.0 -72- .uouuo mcavcaon mo 0030000 mmn.mm 00 30300 0030:300 0 .0es3umu3ca0 0:0 03oono0 0:3:3003 .0co3320300c3 .003ucmma 00000 0: 00:303o: 0:03 0:0 .003533 >000 0030030 00000030 .000330>00000 >000333E :3 00000000 00:30:3 000: 000:000 .00000 :030000000 0:0 0x000 >33uogws< :0033oao030: 0:0 000000 :000000000 0:0 0x000 .0000uo0 3000000 0:0 03000 00:3oc3 000: :033nam: .mnoH .mcwmcnq .:o300>u00:o0 mo 0:0Euuaa0a :0032032 .0003 31mm: Nuqmdm 3000:0m n .0003 .m:30:03 .0:03003ano pmom >pcsoo .pc05300000 >03Lm3: ovapm :0032032 .vuon0m 000umoua 30:::< 00330 5600 mood you 000 00000000 0000 >pc:ou .nmo3 00:30:03 .vc0200000o >03203: ouuum :0032033..nnmd 300000332 0:33xcsuh 00030 30ouzom 0 0.00 0.0 3.03 000.000.3 000.00 000.000 0000.00 003.000 000.00 000.000.3 03.300 0.00 0.00 0.00 000.000 000.03 000.3 000 000.33 000.3 000.000 000.: 3.00 0.0 0.33 300.00 003.0 300.03 000 000.03 000.3 000.00 3.003000; 0.00 0.3 0.0 000.00 00 000 000 033.03 000.3 003.0 00300 00> 0.03 0.3 0.0 000.00 000.3 000.03 000.3 000.03 000.0 000.0 .300.00 0.00 0.3 0.0 000.03 003 000.3 000 300.0 000.3 000.0 000.00 .30 0.00 0.0 0.0 030.00 00 000.0 003.3 000.33 000.3 003.00 03.30 .30 0.00 0.0 0.0 000.00 003 000.3 000 030.0 000.3 003.33 00.0.3.300 0.00 0.0 0.0 000.00 003 003.0 000 003.03 000.0 000.03 0.33000 0.00 0.0 0.0 000.00 000 000.0 300 000.03 000.0 003.00 3.03000 0.00 3.0 0.0 000.30 003 000 000 303.33 000.3 000.0 03.330 0.30 3.30 0.00 000.003 003 000.00 300 000.03 000.0 000.033 00.3300 0.00 0.03 0.00 000.00 000 030.03 000 000.0 000.3 000.00 0000.002 0.00 0.0 0.0 300.00 --- 000.03 000 000.33 300.3 000.0 03.0300: 0.00 0.0 0.0 000.00 000 000.0 003.3 000.0 000.3 000.03 000002 0.00 0.0 0.03 000.30 --- 000.00 030 000.0 000 000.03 00.303: 0.00 0.03 0.00 000.00 000.0 000.3 300 000.0 000.3 000.30 0000.: 0.03 0.3 0.0 000.30 030.0 000.03 000 000.0 000.3 000.0 003.003>33 0.00 0.0 3.0 000.00 300 000 000.3 000.33 030.0 000.03 002.003 -73- highways in Wayne county is reduced by about one-half.9 Highway acre- age expansion proposed for completion within the next three to eight years will take up approximately 50,000 acres more.10 For railroad mileages and acreages, no information could be found specifying either miles of track or right-of—way width, by county, or in total. Mileages of railroads were read off the Conservation Depart- ment maps and converted to acreages based upon an estimated average width of 75 feet for all rail lines, Acreages of land so estimated in railroads, for the study area, amount to less than two-tenths of one per cent of the total non-farm land. The public lands within the study area are made up primarily of state and national forests and game areas, which amount to 210,308 acres. 0f the remainder, 60,905 acres are in state recreation areas, all of which have been acquired since 1940.11 The remainder of the acreage shown as ”public” lands is that acre- age in Metropolitan Authority parks. Although small in total, they are becoming increasingly important in the most heavily populated counties in southeastern Michigan. The area included within such parks totalled ,9Since such a large percentage of Wayne county is urban, a sizeable acreage of land in highways is not tabulated here. Approximately one half of the total highway mileage in Wayne county is urban highway. lOIn 1955, there were 900 miles of highway, 300 feet wide, planned for completion between 1960 and 1965. These are all ne relocation roads. Another 1,200 miles of highway, now 100 to 200 feet wide, are to be widened to 200 to 250 feet. Information obtained in conversation with Henry Ferenz, 9Q. £_1. 11From a tabulation of the State Park System, as of January 1, 1955, by the Michigan Department of Conservation, Lansing, Michigan. -74- 7,480 acres by 1955,12 and will likely continue to expand as population increases and pressure on existing facilities increases. Airports (located outside of city limits) comprise 9,480 acres out of the 49,028 acres included in ”Other" uses° Military reserva- tions (including military airfields) amounted to 15,080 acres, with the balance of 24,468 acres being in various state institutions, training schools and sanitariums.13 When forest and game areas are included as non-farm land, the total of all non-farm land in the study area is considerably smaller than for the remaining counties in the state, as shown in Table 80 State and federal forest and game acreages amount to 278,693 acres, or 14.9 per cent of the total non-farm land, as compared to 90.7 per cent for the non-study area counties. The majority of urban land is located in the area of this study, being nearly 85 per cent of the total urban land in the state, yet this area includes only a little over 42 per cent of the total area of the state. The degree of urbanization also can be seen in figures showing urban land as a percentage of the total land area. In the study area, urban land takes up 1,057,600 acres, or 6.8 per cent of the total area, as compared with the remaining counties in the state where this amounts to 192,430 acres, and only 0.9 per cent of the total area. This total for the urban land in the non-study area counties, however, 12County Maps: 1255, Michigan Department of Conservation, Lansing, l955. 13lbid. -75- Table 8 Acreages of Non-farm Land Uses, by Areas, l955a ‘ AL Type of Use State Study Area Other Counties Urban 1,250,030 1,057,600 192,430 Highways b 120,970 62,724 58,246 County roads 680,524 399,164 281,360 Railroads 59,818 28,527 31,291 Parks and conservationc 7,060,853 278,693 6,782,160 Airports 16,980 9,480 7,500 Military reservations 130,160 15,080 115,080 Othersd 44,370 24,468 19,902 Total non-farms 9,363,705 1,875,736 7,487,969 Total land area 36,494,080 15,505,740 20,987,520 Per cent non-farm 25.7 12.1 35.7 Per cent urban 3.4 6.8 0.9' ‘ Sources: §3§5e Jzunkline Milegge§--Ru;al, Michigan State Highway Department, Lansing, 1955. Third Annual 2;gg;ggg,§gpg;1, Michigan State Highway De- partment, County Road Commissions, Lansing, Dec., 1955. Cougty Maps: 1255, Michigan Department of Conservation, Lansing, 1955. b County road acreages are as of December 31, 1953. c Includes State and Federal forests and game areas, parks and recrea- tion areas, and Metropolitan Authority parks. d Land in Conservation Department Experiment stations and fish hatch- eries, University and Agricultural Experiment Station holdings, and State institutional farms. includes the incorporated area and the subdivided land lying outside the city boundaries as of 1940 only. There has quite likely been some amount of urban expansion in this area, at least for the larger cities. It is possible that recreational developments have taken a considerable amount of land, especially since the late 1940's° Likewise, there may -76- currently be a relatively rapid expansion in residential and business apprOpriation of land as an influence of the construction of the Mackinac bridge. It is recognized that since this area of the state was not mapped, the urban acreage total is understated. If the up-state cities of over 5,000 population experienced the same degree of urbanization as the five check cities mentioned on page 68, there could have been around 17,000 acres taken up by suburban expansion between 1940 and 1955. Quite likely, the expansion in urban and related acreages was somewhat greater than this because of the additional influences mentioned above. Township Changes in Tiers Around Cities Some evidence of effects reaching out from the central city can be found in the relative differences in changes that have taken place within the townships, depending upon their locations with respect to the city. Data have been taken from census reports on population and various kinds of farm information for each of the townships. For purposes of discussion, three separate city areas and their surrounding townships have been selected from among those city areas 14 mapped. Following this, all mapped city areas will be discussed as a group. 14These three cities were chosen for two reasons: Their second tier townships do not overlap those of a nearby city, and their 1950 populations cover the range from 163,143 for Flint, 92,129 for Lan- sing to 11,393 for Hillsdale. -77- £1133. The city of Flint is located centrally in a block of four townships (Genessee, Burton, Flint, and Mount Morris) which make up the first tier. The second tier of townships is made up of Forest, Richfield, Davison, Atlas, Grand Blanc, Mundy, Gaines, Clayton, Flushing, Montrose, Vienna and Thetford. Figure 1 shows the city of Flint and the land area in urban use, as it was mapped. The cross-hatched area is the incorporated area, and the area shaded with diagonal cross-hatchings shows the amount of land that had been subdivided by 1940. The plattings that have taken place from 1940 to 1955 are indicated by the unshaded area lying with— in the outer most boundary line. The incorporated area within the cities of Flint, Mount Morris and Grand Blanc, in 1940, amounted to 20,400 acres. Urban expansion had taken up an additional 4,200 acres by 1940. This amounts to a total area increase of 11.8 per cent by that time. The plattings that have taken place since 1940, shown by the diagonal lines, amount to 22,540 acres -- an increase of 98.9 per cent in total area over a 15-year period. Highway and main road influences upon suburb developments can be seen in the pattern of expansion around the city. Highway 10 running generally north and south through the city, connecting Flint with Saginaw and Pontiac, seems to have exerted considerable influence on home and business location decisions. The suburbs have extended about five miles in either direction along the highway outside the Flint city limits. This compares to expansions of one to three -78— @ = Incorporated Area w: Developed Suburbs, 1940 [:::]= Developed Suburbs, 1955 Scale: One-half inch = one mile Figure 1. Corporate and Suburb Areas, Flint, Mount Morris and Grand Blanc, Michigan. -79- miles in other directions from the city limits. "Paintings" of suburb develOpments can also be noted along highways connecting Flint with Lansing, Owosso, Flushing, and Davison and Lapeer. Such an influence is to be expected, since good roads simply make commuting easier and less time consuming. This makes it possible for people employed within the city to live farther out than those who live along streets and roads that are of poorer construction. The pattern of effect out in the townships is noted in Table 9. In the first tier townships, population increases have been quite large. 0f the individual townships, Burton township made the most rapid gains 6 in total population from 1930 t0‘l950, increasing by 11,444, or 177 per cent, over the 20-year period. The largest numerical increase be- tween ten-year censuses took place during the years from 1940 to 1950, when the population increased by 7,262, an increase of over 66 per cent in that period. The lowest population gain between 1930 and 1950 was shown by Mount Morris township, one which had neither a small city located out in the township, nor a major highway travers- ing through much of the township. Although the numerical gain amounted to 6,457, its percentage increase was 143 per cent from 1930 to 1950, second only to Burton township. -80- Table 9 Population Changes in Townships, by Tiers, Flint City Area8 Farm population Township 1 Total population : RNngopulation : and tier 1 1950 x 1940 311930 3 1950 : 1940 x 1920 : 1950 : 1940 2 1930 First Tier Genese 12,390 8,437 5,889 11,722 6,539 5,227 668 1,898 662 Burton 18,171 10,909 6,727 16,194 9,661 6,300 255 1,248 427 Flint 12,944 9,183 6,320 12,535 7,552 5,313 409 1,631 1,007 Mt. Morris 10,968 6,245 4,511 10,140 4,889 1,940 828 1,356 643 Total 54,473 34,774 23,447 50,591 28,641 18,740 2,160 6,133 2,739 Ave./twp.l3,618 8,694 5,862 12,648 7,160 4,695 540 1,533 685 Second Tier Forest 1,932 1,745 1,481 234 72 -0- 1,068 1,139 1,047 Richfield 3,036 2,361 1,658 2,022 829 447 1,014 1,532 1,211 Davison 3,103 2,372 2,945 2,196 979 802 907 1,393 845 Atlas 1,900 1,660 1,494 961 691 612 939 969 882 Grand Blanc 4,687 3,225 1,948 3,885 1,890 1,005 832 1,335 943 Mundy 2,964 1,884 1,552 1,848 510 519 846 1,374 1,003 Gaines 2,418 2,132 1,858 1,114 756 591 952 1,108 1,017 Clayton 2,146 1,818 1,527 1,065 652 359 1,081 1,166 1,168 Flushing 4,707 3,705 3,298 1,343 435 285 1,138 1,464 1,290 Montrose 3,156 2,501 2,072 960 159 95 1,259 1,667 1,354 Vienna 3,993 3,052 2,351 2,840 501 1,376 1,153 2,551 975 Thetford 2,404 1,861 1,405 1,121 436 47 1,283 1,425 1,358 Total 36,176 28,316 23,587 19,589 7,910 6,138 12,472 17,12313,123 Ave./twp. 3,015 2,360 1,966 1,632 659 512 1,039 1,427 1,094 a Source: 1250 United States Census 91 Population: Characteristic; g: the Pepulation, Michigan, United States Department of Commerce, Bureau of the Census, Washington 25, D.C., Vol. II, Part 22, 1952. b Lapeer Heights (population 1,722) reported for the first time in the 1950 census. Burton township rural non-farm pOpulation for 1930 and 1940 is thus overstated by the population of that village in those years. The growth of the rural non-farm population was even more rapid than the total population, since this was partially offset by losses in farm population. Here, again, Burton township experienced the most rapid —81~ gain numerically, showing an increase of 6,495 from 1930 to 1950, but being exceeded in percentage gain by Mount Morris township which increased from 1,940 to 10,140 for an increase of 422.7 per cent. As a whole the first tier townships showed an increase in total pOpulation of 7,756 per township from 1930 to 1950, with 4,924 of that increase occurring from 1940 to 1950. The average rural non-farm population per township increased 7,953 between 1930 and 1950, with two-thirds of that gain occurring since 1940. The townships showed a substantial increase in farm population from 1930 to 1940, and a sizeable loss from 1940 to 1950, with an overall loss averaging 145 per township over the 20-year period. It is possible that this is simple due to changing economic conditions between census periods, rather than a result of people moving on and off farms as the enumeration might suggest.15 Quite likely, a number of pe0p1e were attempting to carry on agricultural Operations at the time of the 1940 census that had not done so in the previous census period. Likewise, the drop in farm population from 1940 to 1950 may 5To be counted as a farm in the 1940 census required only that a place of more than three acres produce agricultural products with a value of $250 or more, either for home use or for sale. For places of over three acres no minimum product value was required. A change in farm definition for 1950 also eliminated some places counted as farms in 1940. In 1950, places of more than three acres with less than $150 output value were not counted as farms. Places of less than three acres were counted as farms only if the value of products sold was more than $150. This change in definition elimi- nated 12,260 places with agricultural operations, most of which would have been counted as farms in the earlier census. (See: 1250 mmmuw u ue.¥.9.lmsl.1.._as_66 “13:29.21. United States Department of Commerce, Bureau of the Census, Washing- ton, D. C., 1952, pps. xxx to xxxiii.) -82— be due to these people feeling that their incomes were not in need of being supplemented by agricultural Operations by the time the 1950 census was taken. The ”back to the farm movement" that took place during the 1930‘s would also have its effect on the number of farms in the different census periods. Other things remaining unchanged, as more and more people moved back into agriculture during that period, farm numbers for 1940 would be greater than for 1930. Also, as this trend was reversed, 1950 farm numbers would be lower than 1940. That this factor may have been quite influential can be seen in farm numbers for the three census periods as presented here for the Flint area. This can also be noted in the data to be presented for other study area townships. Second tier townships experienced the same directions of change as those in the first tier, but not to as large a degree. While total pOpulation per township in the first tier increased by 7,756, the average increase per township in the second tier was only 1,049. Neither were there such wide differences between townships in the second tier as there were in those of the first. The rate of rural non-farm population increase in the second tier was considerably higher as a percentage than the first tier, yet their numerical increase was much smaller. The average rural non- farm pOpulation increase amounted to 1,120 per township for the second tier, being less than one-seventh that of the first tier. -83; Farm population changes in the second tier were somewhat similar to those of the first tier, but at a lesser rate. From 1930 to 1940 the average farm pOpulation per township increased by 333, and de- clined by 385 from 1940 to 1950. Overall, the second tier townships averaged a five per cent loss in farm population for the 20-year period between 1930 and 1950, compared with a 21.2 per cent loss for the first tier townships during the same period. Those second tier townships through which major highways pass showed population changes that were much higher than the other town- ships of that tier. By 1950, Davison, Grand Blanc, Flushing and Vienna townships had more than 45 per cent of the total pOpulation in the second tier, and more than 52 per cent of the rural non- farm population, yet they make up only one-third of the total area of that tier. These four townships showed a per township total pOpu- lation increase of 1,487 and an increase in rural non-farm pOpulation of 1,699 per township, as compared with an 832 increase in rural non-farm pOpulation for the remaining second tier townships. Table 10 indicates some of the effects of urbanization and rural non-farm residence developments on farms in the first and second tier townships. In farms, as well as in pOpulation, certain differences in the degree of change can be noted as distance from the city in- creases. Farm numbers in the first tier townships changed a great deal over the 20-year period of this study. Except for Flint township, -84- .0 .o .coemcdcmmz .msmcmo on“ 60 :mmnsm .66665860 66 ecosupmqwo 6666 .mco4m4p46 44646 46642 .\ .6 66.666 .6664666 .2 «6456450446¢ Mm mzmceo movmvm 66646: 0664 new .0664 .omoM "mousom 6 666.4 666.4 666.4 664.6 666.64 666.6 466.64 664.66 666.64 664 666 666 .6:6\.o>< 666.64 666.64 666.64 666.664 664.664 646.644 646.646 666.466 666.666 664.6 666.6 466.6 46466 666.4 666.4 666.4 666.6 666.6 646.6 666.64 664.64 666.64 664 666 666 64664666 666.4 666.4 646.4 464.6 666.6 666.6 666.64 666.64 666.64 664 466 666 macco4> 666.6 466.4 466.6 666.6 646.6 666.6 666.64 666.64 666.64 666 666 666 6.644662 666.4 466.6 666.6 644.6 666.44 646.64 666.64 666.46 666.64 664 666 466 6:46.646 666 664.4 666 666.64 664.64 666.64 666.64 666.46 666.64 464 466 664 6646646 666.4 446 666.4 666.64 646.64 646.44 646.64 446.64 466.64 664 664 664 6664.6 664.4 666.4 466.4 666.44 644.64 666.44 666.64 646.46 666.66 664 466 666 666:: 666.4 666.4 666 666.6 464.64 666.6 666.64 646.64 446.64 464 666 464 66.46 66646 666.4 666 666.4 664.6 664.64 666.6 666.66 666.66 446.66 664 664 664 .6446 446 666.4 666.4 666.6 664.64 466.6 466.64 666.64 646.64 664 666 666 com4>66 646.4 666.6 666.4 666.64 666.6 666.6 666.64 646.64 666.64 446 666 466 646466646 666.6 666.4 666.4 466.6 666.6 666.6 666.64 666.46 666.64 666 666 666 466466 Hmwv vcoomm 666 666.4 666.4 666.6 666.6 666.6 666.44 666.64 666.6 644 666 664 .6:4\.o>< 466.6 664.6 666.6 664.66 666.66 666.66 666.66 466.66 646.66 666 466.4 666 46666 644.4 666 666.4 666.6 666.6 666.6 666.44 666.64 666.64 664 666 646 64.462 .4: 666.4 666 666 666.6 666.6 666.6 646.64 666.44 666.6 664 466 664 66446 666 466.4 666 666.6 666.6 666.6 666.6 466.6 646.6 66 666 664 664.66 666 666.4 666.4 666.6 666.6 646.6 646.64 664.64 666.44 664 666 646 66.6666 .644 66446 6664 .6664 .6664 .6664 ..6664 .6664 46664 .6664 .6664 .6664766664 .6664 . 4644 6:. 6464 6:64d640 wOWmHU640 «c44m .6464H 6456:306 >2 .mdflcmczoh c4 momc6£0 546m 04 oanmh -85- all townships in this tier show an increase in farm numbers between 1930 and 1950. As a group, these townships averaged almost a 50 per cent increase in number of farms, increasing from 115 per township to 172. These townships experienced changes different from first tier townships for all city areas as a group, as will be shown later in Table 16. The total of all city areas show a loss in number of farms in the first tier townships from 1930 to 1950. First tier townships around Flint, however, showed an increase of 57 farms per township over the 20-year period. Total acres in farms changed somewhat over the period from 1930, increasing by 1940 and declining more sharply by 1950. Coupled with the changing number of farms, the average farm size for the first tier declined substantially from 1930 to 1940, falling from 98.7 acres per farm to 37.5 acres. By 1950, average farm size had increased to 57.6 acres per farm. Acreages of cropland from which crops were harvested in each of the three census years were approximately 55 per cent of the total acres in farms. Cropland that was lying idle was reduced slightly from 1930 to 1950. Idle cropland per farm in the first tier townships was 7.3 acres per farm in 1930 and 6.3 in 1950. As a proportion of total crop- land from which cr0ps were harvested, however, idle cropland increased from 12.9 per cent in 1930 to 19.4 per cent in 1950. Second tier townships experienced changes similar to those of the first tier, but, as with population changes, the degree of change was not so large. —86- The number of farms per township increased from 176 in 1930 to 224 in 1950, being a 27.3 per cent increase from 1930, but a drop of 24.3 per cent from 1940. Total acres in farms increased slightly over the 20 years, as did the acreage of crOpland harvested. The average acreages per farm were reduced from 1930 to 1950 in both total acres in farms, and in crOpland harvested. In these townships, as in those of the first tier, cropland harvested made up a little over 50 per cent of the total acres in farms, with idle cropland amounting to less than ten acres per farm. In general, there were more farms per township in the second tier than in the first, with farms being larger and having more acres of cropland from which crops were harvested. With the additional competi- tion for land from non-farm sources, we would expect a smaller total area of land to be available for farms in the first tier townships than in the second tier. And with competition bidding up land prices, first tier farms would likewise tend to be smaller than farms in the second tier. Langing. The city of Lansing, shown in Figure 2, takes up most of the area of Lansing township, referred to in Table 11 as the center township. The first tier is made up of the eight surrounding townships (Bath, Meridian, Alaiedon, Delhi, Windsor, Delta, Watertown and DeWitt). Beyond these are the surrounding second tier townships (Sciota, Wood-' hull, Williamston, Wheatfield, Ingham, Vevay, Aurelius, Eaton Rapids, Eaton, Benton, Oneida, Eagle, Westphalia, Riley, Olive, and Victor). -37- Incorporated Area Developed Suburbs, 1940 ‘ Developed Suburbs, l955 Scale: One-half inch = one mile Figure 2. Corporate and Suburb Areas, Lansing and East Lansing, Michigan. ~88- The incorporated area including the cities of Lansing and East Lansing in 1940 amounted to approximately 9,780 acres. Plattings that had been laid out prior to 1940 amounted to 3,380 acres. Plattings completed between 1940 and 1955 totalled approximately 13,960 acres. This is an area expansion since 1940 of more than 140 per cent, as compared with the pre-l940 expansion of almost 35 per cent over the incorporated area. Here, as with the Flint suburbs, highways show considerable influ- ence upon suburb spreadings. The built-up area extends eastward beyond Okemos (approximately two miles beyond the East Lansing city limits, or about five miles beyond the Lansing city limits)./ South of Lansing, the suburb area extends for more than four miles beyond the city limits toward Mason, and about two and one-half miles in the direction of Eaton Rapids on Highway 99. Other highway approaches to Lansing show lesser extensions of the suburbs, reaching out no more than two miles to the west and north. In addition to the suburb areas mapped, "string” plattings extended several miles beyond the suburbs of Lansing and East Lansing. In some locations, homes were quite closely spaced, but in most they were spotted along the highway frontage at irregular intervals. J Table 11 shows some of the changes in pOpulation that have taken place in the townships included in the center, first, and second tiers. Lansing township shows a considerable change in total population from 1930 to 1950. From 1930 to 1940, the population increased 67.6 per cent, followed by an additional increase of 23.5 per cent from P0pulation Changes in Township Tiers, Lansing Area -89- Table 11 a Township: TotaT population : RNngopulation : > Farm nonulation 19501:_l940 : 1930174195011_1940 :11930 and tier: 1950 111940 : 1930 : Center twp. . Lansingb 17,627 14,274 8,518. 17,333 13,651 8,188 294 623 330 First tier . Bath 2,804 1,626 1,033 1,864 831 279 940 - 795 754 Meridianb 9,180 4,767 2,878 8,272 3,485 1,937 836 1,282 941 Alaiedon 1,480 1,132 1,011 430 381 75 1,056 751 936 Delhi 10,077 6,723 4,512 8,781 5,105 3,553 1,296 1,618 959 Windsor 2,628 2,114 1,798 735 296 25 1,119 1,214 1,228 Delta 4,131 2,618 1,921 3,158 1,487 730 973 1,131 1,191 Watertown 1,585 1,219 1,196 816 277 178 769 942 1,018 DeWitt 4,896 3,210 2,545 3,283 1,470 35 789 1,089 2,034 Total 36,787 23,409 16,894 27,339 13,332 6,812 7,778 8,822 9,061 Ave./twp. 4,598 2,926 2,112 3,417 1,667 852 972 1,103 1,127 Second tier Sciota 1,640 1,544 1,324 34 -0- -0- 664 738 619 Woodhull 1,053 887 625 358 306 95 695 581 530 w1111amston1,175 2,682 2,291 465 130 183 710 848 750 Wheatfield 761 821 776 107 86 114 654 735 662 Ingham 1,203 1,095 995 132 97 -o- 638 647 707 Vevay 1,114 1,035 938 119 70 48 995 965 890 Aurelius 1,482 1,316 1,109 389 197 241 1,093 1,119 868 EatonRapidsl,3ll 1,103 1,033 366 -o- 232 945 1,103 801 Eaton 958 838 823 207 6 112 751 832 711 Benton 1,660 1,442 1,319 237 61 94 799 834 733 Oneidab 1,552 1,269 1,169 745 237 284 807 1,032 885 Eagle 1,098 1,109 1,011 266 -o- 125 678 963 763 Westphalia 1,417 1,297 1,249 .120 -0- -o- 838 940 943 Riley 896 867 875 257 8 69 639 859 806 Olive 1,142 1,012 945 298 12 51 844 1,000 894 Victor 976 898 769 211 112 97 765 786 672 Total 19,429 19,215 17,251 4,311 1,322 1,745 12,515 13,982 12,234 Ave./twp. 1,214 1,201 1,078 269 83 109 782 874 765 a Source: 1250 United State§ Censug 91 P0 uia o : Characteristics 2: LEE Pnnulation, Michigan, United States Department of Commerce, Bureau of the Census, Washington, D. C., Vol. II,‘Part 22, 1952. b Part of Lansing township annexed to Lansing city in 1949, and to East Lansing city in 1944 and 1949. Part of Meridian township annexed to East Lansing city in 1940, and part of Oneida township annexed to Grand Ledge city in 1947. -90- 1940 to 1950. The numerical gain from 1930 to 1940 was 5,756, con- siderably larger than the increase of 3,353 from 1940 to 1950. Rural non-farm population changes took place at about the same rate as total population, increasing 66.7 per cent from 1930 to 1940, and 27.0 per cent from 1940 to 1950. The numerical gain was slightly less than for total pOpulation, but here, again, the most rapid gain occurred between 1930 and 1940. Approximately 60 per cent of the total increase in rural non-farm population took place in the first ' ten years following 1930. Rural non-farm pOpulation increased by a greater percentage between 1930 and 1950 than total popdlation, being partly offset by a 10.9 per cent reduction in farm pOpulation.during this period of time. Townships in the first tier experienced population gains that were quite rapid, but under a different growth pattern than the center town- ship. Where two-thirds of the center township's total population growth took-place during the first ten years of this study period, about two- thirds of the growth in total population in the first tier townships occurred in the last ten years. The increase per township amounted to 117.7 per cent over the twenty years from 1930; a higher rate than in the center township, but numerically, considerably less with the pOpulation increase averaging 2,486, compared with 8,869 for the center township. The rate of increase in rural non-farm pOpulation in the first tier townships was much more rapid than their total population increase. As a whole, these townships increased their rural non-farm pOpulation -91- by more than four times, showing a growth from 852 per township in 1930 to 3,417 in 1950. Four of the townships (Meridian, Delhi, Delta, and DeWitt), through which major highways pass, exhibit much more rapid rates of growth than the remaining four townships in the first tier. In 1930, these four townships had 70.2 per cent of the total pOpulation; by 1950, they had 77.1 per cent. Where the 1930 to 1950 increase in population for these four townships were 139.4 per cent, the remaining four showed an increase of 67.0 per cent. Similarly, in 1930 they had 67.5 per cent ofothe rural non-farm pOpulation, and by 1950 their percentage had risen to 85.8. The rural non-farm population increase in these townships was 410.4 per cent while the remaining four showed an increase of 74.9 per cent. In 1930, these four townships included 54.5 per cent of the total farm pOpulation in the first tier, with this percentage falling to 51.4 per cent by 1950. As with Flint, Lansing's second tier townships exhibit changes generally similar to the first tier, but at a considerably lower rate. Total population per township averaged an increase of only 12.6 per cent from 1930 to 1950, with a numerical increase of only 136 per township. Similarly, rural non-farm population, although increasing 146.8 per cent per township, amounted to only 160 over the twenty years. Farm population increased slightly in the second tier, compared with an average township loss in farm pOpulation of 13.8 per cent in the first tier townships. -92- Table 12 Farm Changes in Townships, by Township Tiers, Lansing Areaa Township : Number of farnni, : Tota acres 1 farms _fi 4nnng_tier : 1950 1940 1.21930 : 1950 12,1940 1930 Center the Lansing 46 170 105 2,310 5,617 6,158 First tier Bath 163 203 160 16,151 17,648 16,560 Meridian 144 260 178 11,538 18,082 16,071 Alaiedon 191 181 217 20,020 18,224 21,673 Delhi 198 297 226 16,405 17,748 16,267 Windsor 219 238 254 19,088 19,617 21,340 Delta 188 227 235 17,000 18,150 19,419 Watertown 208 195 238 19,817 19,611 22,031 DeWitt 152 247 175 17,344 17,855 19,339 Total 1,463 1,848 1,683 137,363 146,935 152,700 Ave./twp. 183 231 210 17,170 18,367 19,088 Second tier Sciota 132 150 151 14,959 14,921 16,715 Woodhull 131 138 131 13,937 16,350 14,914 Williamston 164 179 153 18,136 17,152 17,161 Wheatfield 129 130 156 16,841 18,568 18,570 Ingham 135 150 154 16,997 19,031 18,322 Vevay 150 200 241 17,514 19,424 21,471 Aurelius 202 191 224 20,760 21,187 21,543 Eaton Rapids 203 212 190 21,911 21,022 18,963 Eaton 181 179 202 19,820 19,002 20,037 Benton 193 195 182 20,017 21,447 20,924 Oneida 186 226 222 19,244 21,202 19,385 Eagle 151 182 165 19,004 22,156 20,971 Westphalia 149 174 174 20,797 22,588 22,258 Riley 156 166 180 20,475 20,546 21,120 Olive 194 206 216 20,965 22,270 21,976 Victor 163 190 173 19,851 21,171 19,976 Total 2,619 2,868 2,914 303,228 316,337 313,676 Ave./twp. 164 179 182 18,952 19,771 19,605 a Source: 1930, 1940, and 1950 United States Census 9: Agriculture: Minor Civil Divisions, Michigan, United States Department of Commerce, Bureau of the Census, Washington, D. C. -93— Table 12 continued. Township : Acres of crOpland harvested : Acres of cropland idle and tier 1, 1950: 1940 : .1930 : 1950 : 1940 .1 1930 Center twp. Lansing 1,127 2,931 3,256 331 564 927 First tier Bath 6,140 7,227 7,195 1,327 1,414 1,597 Meridian 5,199 8,114 7,744 979 1,256 1,817 Alaiedon 11,182 10,296 11,462 2,131 714 1,488 Delhi 8,153 9,261 8,342 1,724 1,321 2,116 Windsor 10,366 10,114 11,203 1,996 1,143 1,698 Delta 8,936 9,345 10,599 2,088 1,060 1,448 Watertown 10,711 10,810 12,183 1,415 731 1,554 DeWitt 9,231 9,774 10,996 2,063 1,364 628 Total 69,918 74,941 79,724 13,723 9,003 12,346 Ave./twp. 8,740 9,368 9,966 1,715 1,125 1,543 Second tier Sciota 7,502 7,393 7,817 1,424 2,535 1,417 Woodhull 5,281 5,215 6,094 1,559 1,151 1,294 Williamston 9,674 8,256 8,973 1,147 1,334 465 Wheatfield 8,916 9,607 9,583 1,120 466 1,370 Ingham 8,824 8,504 8,559 1,416 1,115 1,581 Vevay 9,239 9,435 11,120 1,452 583 1,324 Aurelius 11,238 11,329 11,242 1,614 500 1,358 Eaton Rapids 10,885 10,041 9,404 1,450 583 1,228 Eaton 9,996 9,444 10,245 1,525 951 1,655 Benton 12,027 11,106 10,945 1,349 727 959 Oneida 11,894 12,005 11,274 1,099 609 ,1,408 Eagle 10,629 11,985 11,815 870 775 971 Westphalia 12,592 12,799 12,060 368 938 1,013 Riley 12,684 12,058 11,616 469 454 1,340 Olive 11,446 12,006 11,959 1,488 1,096 1,559 Victor 8,529 9,063 9,017 2,158 950 1,900 Total 161,356 160,246 161,723 20,508 14,767 20,842 Ave./twp. 10,085 10,015 10,108 1,282 923 1,303 -94- Farm changes in the center township were quite abrupt due to the urban competition for land. Farm numbers were reduced by 59 from 1930 to 1950, with the average farm size also falling to 50.2 acres from the 1930 average of 58.9 acres. Acreages of cropland harvested fell by 2,129 acres, with about 90 per cent of that reduction coming after 1940. Farm numbers per township in the first tier were considerably greater than in the center township, with average farm size also being much greater. While the average size of farms in the center township was reduced in both 1940 and 1950, farms in the first tier townships also declined in 1940, but reversed that trend in 1950, increasing about three acres over the 20-year period. Cropland harvested per farm in the first tier averaged almost double that of the center township. Of the total acres per farm, first tier farms by 1950 were using 50.9 per cent of their land for crOpping, compared with 48.8 per cent for the center tier. Second tier farmers used a slightly larger proportion of their land in farms for cropping than this. Crapped land amounted to 61.5 acres per farm, or 53.2 per cent of the total acreage. The proportion of land used for crops declined only slightly but steadily from 1930 for the center and first tier, while the second tier farmers have increased the proportion of land harvested from the 51.6 per cent cropped in 1930. Farms in the second tier were not as numerous as in the first tier, and averaged somewhat larger. Second tier farms averaged 115.6 acres by 1950, compared with 93.8 acres per farm for the first tier and 50.2 i -95- acres for the center township. Where average acres in farms in the first tier drapped by 1940, those in the second tier increased in both lO-year periods, rising by about three acres per farm from 1930 to 1940 and approximately five acres more by 1950. Idle cropland seemed not to be affected by township location. In all townships, idle crOpland was less than ten acres, being 7.2 acres per farm in the center, 9.4 acres in the first tier, and 7.8 acres in the.second tier townships. £1. Elgnnnnt. Urban acreages in and around the city of Mt. Pleas- ant are shown in Figure 3. The incorporated area of the city amounted to 2,180 acres in 1940. Plattings laid out prior to 1940 were approxi- mately 80 acres, which apparently were not very densely settled at that time. The acreage taken up by new develOpments between 1940 and 1955 totalled approximately 1,200 acres, an area expansion of more than 50 per cent over that occupied by 1940. Most of the new develOp— ments extend out less than two miles along Highway 20 from Midland, and south about one mile from the city limits on Highway 27 toward Shepherd. Other small developments extend out no more than one- fourth mile to the west, wouthwest and southeast of the city. Union township, within which the city of Mt. Pleasant is located, also includes all the area over which urban use around the city has expanded. Most of the changes in this township, as well as those in the first and second tiers have been relatively slow when compared with changes in the townships around Flint and Lansing. With a much smaller urban population, and relatively little urbanization, the = Incorporated Area fl = Developed Suburbs, 1940 1 — 1—1 = Developed Suburbs, 1955 Scale: One-half inch = one mile Figure 3. Corporate and Suburb Areas, Mount Pleasant, Adrian, Owosso and Corunna, Michigan. -97- effects out in the townships would also be much less than in the other city areas. Population data for the townships around the city of Mt. Pleasant are presented in Table 13. The 1950 total population of Union town- ship was a little more than double that of 1930, increasing by 1,316 during that period of time. Rural non-farm population growth was somewhat larger, being a 20dyear increase of 1,535. This was partly off-set by a farm p0pulati0n loss of 219 during the same period. First tier townships increased their total population by only 19, and their rural non-farm population by 119, which is considerably lower than for the center township. Township population gains in this tier were also less than those in the second tier. In both tiers there was close to a ten per cent loss in farm population. As with population changes, adjustments in farms and acreages were also made at a lower rate than in the Flint and Lansing areas. As indicated in Table 14, the center township showed a reduction in total acres in farms and crOpland harvested, as well as in the number of farms. In spite of this, farms averaged 123 acres in 1950, compared with 82.3 acres in 1930, with slightly more than one-half of this acreage used for crops. First and second tier townships also showed fewer farms in 1950 than in 1930. Average size in the first tier was increased by almost 10 acres to 116.7 acres per farm, while those of the second tier in- creased by 18.5 acres to 124 acres per farm. Farms in both tiers in- creased their acreages of cropland harvested, with those of the first -98- Table 13 a Population Changes in Township Tiers, Mt. Pleasant Area pooulntion : RNngopulation : Farm nonulation 1940 : 1930 : 1950 :21940 : 1930 : 1950 :n1940 : 1930 Township : Total _§nd_tier : 1950 : Center two. Union 2,596 1,767 1,280 1,758 570 223 838 1,197 1,057 First tier Denver 799 916 775 147 299 152 652 617 623 Chippewa 1,151 1,191 918 298 4 242 853 1,187 676 Coe 2,046 2,128 2,130 181 63 155 966 1,213 1,136 Lincoln 1,021 1,097 1,037 252 208 82 769 889 955 Fremont 885 901 825 194 151 145 691 750 680 Deerfield 842 882 856 248 39 34 594 . 843 822 Nottawa 1,263 1,358 1,302 417 219 329 846 1,139 973 Isabella 1,381 1,456 1,394 606 275 250 775 1,181 1,144 Total 9,388 9,929 9,237 2,343 1,258 1,389 6,146 7,819 7,009 Ave./twp. 1,174 1,241 1,155 293 157 174 768 977 876 Second tier Warren 872 792 655 159 87 12 713 705 643 Geneva 623 613 620 157 67 126 466 546 494 Greendale 751 850 536 395 513 304 356 337 232 Jasper 735 810 704 176 218 51 559 592 653 Bethany 1,205 1,293 1,258 264 12 35 941 1,281 1,223 Pine River 1,459 1,181 1,093 703 127 194 756 1,054 899 Seville 1,498 1,428 1,315 768 619 370 730 809 945 Richland 1,125 1,029 900 461 307 207’ 664 722 693 Home 1,955 1,896 1,907 147 65 149 837 1,006 861 Rolland 942 1,032 1,004 283 286 314 659 746 690 Broomfield 616 738 670 59 10 4 557 728 666 Sherman 682 887 720 292 254 302 390 633 418 Coldwater 619 628 677 122 32 44 497 596 633 Gilmore 566 610 496 31 19 17 535 591 479 Vernon 1,092 1,071 955 315 98 96 777 973 859 Wise 1,070 907 876 259 51 81 811 856 795 Total 15,810 15,765 14,386 4,591 2,765 2,306 10,248 12,175 11,183 Ave./twp. 988 985 899 287 173 144 641 761 699 a Source: 1950 Unite} S ates Census 91 Pgnulation: Characteristics 9: Pgnulation, Michiqgn, United States Department of Commerce, Bureau of the Census, Washington, D- C-, V01. 11, Part 22, 1952. b Part of Pine River township annexed to St. Louis city in 1947. -99- Table 14 Farm Changes in Townships, by Township Tiers, Mt. Pleasant Areaa j :- Township : Number of farms : Total acres in farms and tier 1950 : 1940 : 1930 1950 1940 .;_ 1930 Center Union 143 203 228 17,592 17,161 18,753 First Tier Denver 139 132 113 14,857 13,696 11,688 Chippewa 151 189 150 14,015 13,695 13,369 Coe 208 217 235 22,302 22,389 22,998 Lincoln 172 190 202 21,042 21,080 21,161 Fremont 151 165 150 19,119 21,259 18,924 Deerfield 116 152 146 14,085 17,180 16,540 Nottawa 160 183 161 21,687 21,342 18,716 Isabella 169 215 193 20,455 21,705 21,055 Total 1,266 1,443 1,350 147,562 152,346 144,451 Ave./twp. 158 180 169 18,445 19,043 18,056 Second tier Warren 172 181 150 16,359 17,716 13,048 Geneva 110 115 119 12,139 11,449 10,951 Greendale 56 47 45 6,708 3,629 3,735 Jasper 110 134 130 13,250 13,875 14,145 Bethany 227 238 253 22,333 22,248 20,537 Pine River 169 226 214 19,409 21,315 20,260 Seville 162 199 212 20,076 18,736 19,858 Richland 136 149 156 14,540 16,247 15,683 Home 163 217 191 17,498 18,792 17,736 Rolland 137 _141 147 18,610 17,538 17,518 Broomfield 132 138 132 18,733 16,848 16,881 Sherman 77 88 97 14,722 12,250 13,714 Coldwater 98 116 127 15,560 16,997 18,135 Gilmore 86 114 110 13,133 13,627 13,536 Vernon 153 184 171 23,349 23,266 21,135 Wise 144 179 145 17,439 19,161 16,229 Total 2,132 2,466 2,399 263,858 262,694 253,101 Ave./twp. 133 154 150 16,491 16,418 15,819 a Source: 1930, 1940, and 1950 United States Census g: Agriculture; Minor Civil Divisions, Michigan, United States Department of Commerce, Bureau of the Census, Washington, D. C. -100- Table 14 continued Township 3 A e o a rves e x A re 0 d id e and tie; ; 1259 is. 1940 i 1930 1 11950 il_1940 51,119§Q__ Center twp. Union 9,567 10,140 11,762 673 548 1,072 First tier Denver 7,823 7,462 7,093 493 358 487 Chippewa 7,136 6,798 6,756 497 1,067 695 Coe 14,382 14,438 14,769 550 382 635 Lincoln 12,069 11,639 12,180 722 914 989 Fremont 8,665 8,850 8,626 1,518 960 1,221 Deerfield 6,216 7,501 8,300 863 773 1,014 Nottewa 12,046 11,763 11,221 606 1,274 460 Isabella 12,086 12,493 11,956 986 312 841 Total 80,423 80,944 80,904 6,235 6,040 6,342 Ave./twp. 10,053 10,118 10,113 779 755 793 Second tier larren 6,243 6,287 5,067 1,050 389 572 Geneva 5,067 4,413 4,394 278 559 809 Greendale 940 1,090 1,068 840 186 134 Jasper 7,282 6,962 7,274 582 332 363 Bethany 15,341 14,837 13,454 518 176 739 Pine River 11,943 11,783 11,565 806 336 974 Seville 9,335 10,060 9,581 1,423 580 2,674 Richland 5,037 5,670 6,230 1,507 1,833 1,745 Home 8,143 8,595 8,849 1,925 1,298 1,342 Rolland 7,682 7,000 7,379 1,437 1,742 1,069 Broomfield 6,788 6,650 7,349 2,457 1,346 850 SShermen 3,883 3,380 4,831 1,124 21 1,132 Coldwater 5,218 5,699 6,881 1,610 695 705 Gilmore 4,419 4,916 5,374 867 806 846 Vernon 10,914 10,567 10,268 1,465 213 485 liee 9,159 8,563 7,650 531 196 1,594 Total 117,394 116,472 117,214 18,420 10,758 16,033 Ave./twp. 7,337 7,280 7,326 1,151 672 1,002 —101- tier utilizing a somewhat larger prOportion. More than one-half of the total farmland in the first tier was used for cropping, and second tier farmers used less than 45 per cent of their total farmland for crops. In the Mt. Pleasant area, as in the Flint and Lansing areas, idle cropland amounted to less than 10 acres per farm, and in the center and first tier, was less than five acres per farm. Little change in this acreage occurred over the twenty years from 1930. All mapped city areas. Acreage changes in urban land have been presented in Table 5 above. Figures 4 through 14 show the city areas that were mapped, from which acreage estimates of the degree of urbanization have been made. For most of the city areas, the influence of highways and improved roads shows quite plainly. Housing developments extend further out from the city limits along these roads, while being retarded in the areas between. This influence is much more noticeable around the larger cities, but is not entirely absent around the small cities of the study area. G Another strong effect upon the direction of suburb expansion is the location of another city nearby. In pairs of cities such as Ann Arbor and Ypsilanti, Detroit and Pontiac, Detroit and Mt. Clemens, Bay City and Saginaw, and smaller cities such as Owosso and Corunna, much of the development has taken place between these cities. Suburb develOp- ment activity seems stronger in such between-cities areas than else- where. -102- .5356“: .3532; “Em “on: SE .392 nusnzm new 393980 JV 0.33"" 3?. mac n soc“ 32120 333 mom; .mnnsnsm pmaoHo>oo HE ovofi .mnnsnzw vodoflm>oo u @ mm: 63223005 HE -103... Incorporated Area igggs = Developed Suburbs, t 940 = Developed Suburbs, l955 Scale: One—half inch = one mile Figure 51 Corporate and Suburb Areas. Battle Creek, Michigan. -th- Incorporated Area Developed Suburbs, 1940 Developed Suburbs, 1955 Scale: One-half inch = one mile Figure 6. Corporate and Suburb Areas, Bay City and Essexville, Michigan. -105- H Incorporated Area Developed Suburbs, 1940 [:::] Developed Suburbs, 1955 Scale: One-half inch = one mile Figure 7. Corporate and Suburb Areas, Benton Harbor, St. Joseph, Shoreham and Jackson, Michigan. = Incorporated Areo =Developed Suburbs, I955 Approximate Scale: 0J5 inch -one mile -lO7— Q E = Incorporated Area @ = Developed Suburbs, l [:::] = Developed Suburbs, l955 Scale: One—half inch = one mile Figure 9. Corporate and Suburb Areas, Grand Rapids and East Grand Rapids, Michigan. -108- ,3¢%§= Incorporated Area 244+ EEE§§= Developed Suburbs, 1940 , .V. l I: Developed Suburbs, 1955 Scale: One—half inch = one mile Figure 10. Corporate and Suburb Areas, Kalamazoo, Michigan. ~109- Incorporated Area Developed Suburbs, 1940 Developed Suburbs, 1955 Scale: One—half inch = one mile Figure 110 Corporate and Suburb Areas, Monroe, Michigan. .cmmwcofiz .mpnmfio: commxmsz pcm comoxmaz nwuoz .comox .m nusnsm new opmnoqaoo .NH oazmfim HHS oco I coca was; one «mamum mom; J. .wnuansw poao~o>ma u ovow .mnnsnsm no o~o>oa u I] D mmH< pmumuodnoocH u -llO- -111- . Ti -- 1'13 .. LJ 1 -1— Incorporated Area at. 6+ F... Developed Suburbs. 1940 .8 H F _] I t.__J L : Developed Suburbs, 1955 Scale: One-half inch = one mile Figure 13 Corporate and Suburb Areas, Port Huron and Marysville, Michigan. ll ~112- Incorporated Area Hie half arch : one mile 14 cc;p;ra:e and Schlb Areas, Saginaw, Michigan. -113- In addition to the suburb expansions that have taken place are the “string" plattings along highway approaches to the cities. These plattings extend far beyond the suburbs that have been develOped° In most of such cases, individuals have simply purchased enough land front- ing on highways to meet their needs for space. In some areas these plat- tings become almost continuous, but in most instances are quite irregular- ly spaced. The highway frontage from Bay City to Midland, for example, is quite heavily platted, a distance of approximately 12 miles from the Bay City suburbs to the Midland city limits. A number of other high- ways are similarly settled, but usually of somewhat lesser density. Information on the population changes that have taken place in the townships is presented in Table 15. In this.tabulation, only the ave- rages for each of the townships in a particular location are given. For example, there are 10 cities each of which is located within one township, called the center township. The figures in the table for the center township are averages for these 10 center townships.16 First tier and second tier townships are presented in the same manner, with the township location given clockwise, beginning with the average of all townships lying in a northeasterly direction from the central city. Center townships in the areas mapped averaged a 1950 population of 6,622. This is an increase of more than 90 per cent since 1930. The largest numerical increase occurred from 1940 to 1950, when these townships gained 1,659 per township over 1940. 16For the totals of all the townships, see Appendix Table 8. -ll4— Table 15 Population Per Township, by Township Tiers, All Mapped City Areasa Township : b location : Total population RNF population Farm 0 i and tier 8.1950 : 1940‘11930 : 1950 : 1940 : 1930 : 1950 : 1940.11939 Center twp's. 6,622 4,963 3,429 6,132 3,900 2,773 474 649 660 First tier NE twp's. 7,059 4,224 3,437 5,106 3,035 2,528 856 1,116 .840 E twp's. 5,879 3,601 2,996 2,838 1,340 1,106 843 1,111 938 SE twp's. 5,979 4,068 3,547 3,483 1,857 1,717 783 1,034 831 S twp's. 5,651 3,414 2,843 3,725 2,434 2,141 633 842 664 SW twp's. 6,041 3,806 2,809 4,192 2,689 1,871 696 849 811 U twp's. 6,149 3,431 2,444 5,318 2,427 1,551 688 914 805 NH twp's. 4,268 2,589 1,982 3,388 1,567 880 712 941 771 N twp‘s. 3,508 4,721 4,153 3,952 2,600 3,049 618 916 840 Total 44,534 29,854 24,211 32,002 17,949 14,843 5,829 7,723 6,500 Ave./twp. 5,567 3,732 3,026 4,000 2,244 1,855 729 965 813 Second tier NE twp's. 2,144 1,654 1,347 1,006 563 356 732 793 741 ENE twp's. 2,540 1,931 1,982 1,274 644 787 737 857 811 E twp's. 2,261 1,728 1,469 1,024 329 271 808 1,006 835 ESE twp's. 2,291 1,826 1,587 998 454 288 936 1,062 922 SE twp's. 1,855 1,487 1,307 756 302 182 941 1,057 968 SSE twp's. 2,405 1,830 1,587 1,208 459 342 857 1,056 954 S twp's. 3,082 2,503 1,795 958 928 143 724 766 720 SS“ twp's. 2,472 1,873 1,680 1,069 499 376 913 1,022 928 SW twp's. 2,170 1,779 1,705 969 500 351 926 1,108 968 WSW twp’s. 3,156 2,136 1,605 1,612 739 395 953 1,122 951 I twp's. 7,243 3,852 2,902 3,990 2,010 1,520 713 908 756 ”NW twp's. 2,542 1,847 1,516 1,302 500 402 773 954 755 NW twp's. 1,471 1,220 1,083 474 162 133 786 898 799 NNW twp's 1,765 1,400 1,219 774 247 368 790 979 811 N twp's. 2,226 1,734 1,748 668 220 342 727 854 818 NNE t '5. 2,497 1,203 1,523 1,449 647 347 790 921 779 Totfi 42,120 29,994 26,055 19,531 9,203 6,503 13,097 15,363 13,516 Ave./twp. 2,633 1,875 1,211 1,221 575 406 819 960 845 a Source: 1259 United States Census 9; Population: Characteristics 9: the Pogulatiog, Michi a , United States Department of Commerce, Bureau 0 the Census, Washington, D. C., Vol° II, Part 22, 1952. b In this tabulation there are 53 unincorporated towns and villages and cities incorporated since 1940, with a pOpulation total of 128 621 listed for t e first time in the 1950 census. RNF Opulation 5 there- fore overstated by the total pOpulation of these vi lages and cities in 1930 and 1940. In addition, there were a large number of annexa- tions during this period of time that do not specify the po ulations of the annexed areas, which also overstates the RNF pOpulatgon for 1930 and 1940. -115- Rural non-farm population in the center townships grew at a more' rapid rate than total pOpulation. The townships showed an increase of 121.1 per cent over the 20 years from 1930, and a numerical increase of 3,359 during that time. The greatest increase in this population category was also shown in the years 1940 to 1950. A total of 2,232 rural non-farm residents were added during that time, almost double the 1,127 increase from 1930 to 1940, reflecting the increased em- phasis on residential location outside of the city. Farm pOpulation for the center townships averaged an annual decline of just less than 10 per year, declining 28.2 per cent from 1930. The largest decline occurred from 1940 to 1950 in these townships, while those of the first and second tier showed a decline only in the period from 1940 to 1950. First tier townships showed a farm popu- lation decline of 10.3 per cent from 1930 to 1950, and second tier townships averaged a loss of 3.1 per cent during the same period of time. First tier townships increased their total population by 84 per cent from 1930 to 1950, higher than the 61.7 per cent in the second tier. Numerically, first tier townships showed a 1930 to 1950 pOpu- lation gain more than two and one-half times that of the second tier, while that of the center townships was more than 25 per cent greater than for the first tier. Rural non-farm population also shows the effects of distance upon pOpulation density and population changes. While the 1950 rural non-farm pOpulation totals for the center, first and second tiers -ll6- were 6,132, 4,000 and 1,221, respectively, the increase for the center township amounted to 3,359, for the first tier 2,145, and 815 for the second tier townships. Farm changes that have taken place are presented in Table 16. Because of the method of tabulating farm data in the census, these indicators are not as accurate as would be desired.17 Farms were reduced in number in the first and second tier town- ships, as well as in the center townships, although not so rapidly. While the second tier farm numbers fell by 5.9 per cent from 1930 to 1950, and those of the first tiere were reduced by 8.7 per cent, center township farm numbers fell by 38.3 per cent during that period of time. Farms in the center townships averaged 104.8 acres, an increase of 30 acres per farm over 1930. Because of the error introduced in '— 17Farms located within an area defined as urban by the census are reported separately in the census as ”Other Units", by county, only, without specifying either the urban territory or township within which they are located. A sizeable increase in the number and acreages of land in these other Unit farms results from the changed definition of urban territory in the 1950 census. The following tabulation shows farms as reported by the census only for counties in which there was a city mapped: Number : Total acres: Acres of crop-: Acres of crOp- Year : of farmsri in farms : land harvested: land idle 1950 2,525 109,910 ,54,322 10,719 1940 1,080 40,419 19,712 4,336 1930a 208 11,546 5,301 1,911 a Macomb and Wayne counties only reported. Township tier : -ll7- Table 16 Number of farms ‘- 1 -_ Farm Averages Per Township, by Township Tiers, All Mapped City Areasa b rotil acres in farms and location : 1950 : 1940 : 1930 : 1950 : 1940 : 1930 Center twp's. 100 138 162 10,478 10,774 12,123 First tier NE twp's. 171 238 190 14,240 15,495 14,987 E twp's. 177 226 188 15,348 16,604 15,293 SE twp's. 173 203 179 14,851 15,787 14,994 8 twp's. 122 174 142 11,487 13,278 12,376 ‘ SW twp's. 143 187 166 13,039 14,698 14,383 W twp's. 153 191 171 13,821 16,156 15,710 NW twp's. 155 210 159 15,319 16,976 15,343 N twp's. 135 218 151 14,410 15,863 15,115 Total 1,229 1,649 1,346 112,515 124,842 118,201 Ave./twp. 154 206 168 14,064 15,605 14,775 Second tier NE twp's. 149 180 162 16,515 18,388 17,609 ENE twp's. 159 186 155 15,835 16,873 14,982 E twp's. 181 208 191 15,687 16,327 17,355 ESE twp's. 192 214 191 17,330 17,969 17,246 SE twp's. 189 207 208 19,063 19,066 19,609 SSE twp's. 178 254 195 18,167 19,245 15,116 8 twp's. 170 191 183 18,741 19,523 18,441 SSW twp's. 163 223 174 15,759 18,463 15,772 SW twp's. 196 245 215 17,550 18,882 18,151 WSW twp's. 201 255 219 18,588 18,857 19,458 W twp's. 152 188 177 14,889 17,027 16,739 WNW twp's. 169 212 166 17,654 18,947 17,643 NW twp's. 167 194 183 17,315 18,709 18,760 NNW twp's. 170 190 166 17,063 17,280 16,524 N twp's. 164 184 193 17,152 18,250 19,328 NNE twp's. 161 199 156 15,951 18,046 15,979 Total 2,761 3,330 2,934 273,259 291,852 278,712 Ave./twp. 173 208 183 17,079 18,241 17,420 a Source: 1930, 1940, and 1950 United States Census of Agriculture: Minor Civil Divisions, Michigan, United State Department of Commerce, Bureau of the Census, Washington, D. C. b For the totals for all the townships, see Appendix C. Table 16 continued -118- Township tier 1 Acres of cropland harvested : Acres of cropland idle and location 3 1950 a 1940 s 1930 : 1950 a 1940 x 1930 Center twp's. 5,233 5,263 6,046 4,872 643 1,361 First tier NE twp's. 7,430 7,575 7,747 1,301 1,279 1,367 E twp's. 8,534 8,683 8,101 1,033 1,182 1,370 SE twp's. 8,242 8,480 8,027 1,149 849 1,165 S twp's. 5,622 6,302 5,891 9,921 1,040 1,300 SW twp's. 6,926 7,073 7,190 860 1,257 1,285 W twp's. 7,148 7,853 7,782 1,258 1,097 1,239 NW twp's. 7,787 8,220 7,475 1,343 1,435 1,554 .N twp's. 7,420 10,390 7,455 1,201 1,073 1,477 Total 59,109 64,576 59,668 18,075 9,212 10,757 Ave./twp. 7,389 8,072 7,459 2,259 1,152 1,345 Second tier NE twp's. 8,338 8,270 8,207 1,146 1,235 1,370 ENE twp's. 7,946 7,921 7,461 1,133 1,242 1,335 E twp's. 8,936 8,644 8,883 1,085 1,171 1,578 ESE twp's. 9,535 9,420 9,231 1,347 949 1,223 SE twp's. 10,714 9,339 10,138 1,336 1,055 1,555 SSE twp's. 10,425 10,185 9,389 1,146 910 1,462 S twp's. 9,795 10,426 9,145 1,421 1,028 1,752 SSW twp's. 8,715 9,239 7,964 1,135 1,457 1,322 SW twp's. 9,414 9,581 9,399 1,405 1,433 1,511 WSW twp's. 9,594 9,242 9,800 1,451 1,529 1,555 W twp's. 7,568 8,526 8,121 1,259 996 1,509 WNW twp's. 8,838 9,348 8,536 1,393 1,248 1,389 NW twp's. 8,591 8,830 9,055 1,390 1,184 1,485 NNW twp‘s. 8,851 8,257 8,170 1,155 1,293 1,518 N twp's. 8,577 8,541 9,254 1,145 1,409 1,727 NNE twp's. 7,791 8,237 7,795 1,231 1,365 1,439 Total 143,628 144,006 140,548 20,178 19,504 23,760 Ave./twp. 8,977 9,000 8,784 1,261 1,219 1,485 -119- the census report, average farm size is larger in the center town- ships than for either the first or second tier farms, these being 91.6 and 99.0 acres, respectively, in 1950. (An adjustment of average farm size for the center angifirst tier township farms will be made following the discussion of Table 16.) One would conclude, how- ever, that farm size would likely be much smaller near a city than further out in the Open country. Just as for total acres in farms, the center townships average a larger acreage of cr0pped land per farm than in the first and second tier farms, although the difference is not so great as for total acres in farms. Here, also, one would expect center township crop acres per farm to be smaller than in the other two tiers. Except for the center and first tier townships, in 1950, idle crOpland is a small part of the total acres in farms. In 1950, however, idle crOpland in the center townships farms averaged 48.7 acres per farm, almost as large an acreage as that cropped. First tier farms averaged 14.7 acres of land idle in 1950, just over 16 per cent of the total acreage in farms. For all other years, idle cropland was less than 10 acres per farm, the highest being 8.4 acres in 1930 for center township farms. The relative amounts of farm land per township in the different tiers show the effects of the urban competition for lando Center townships averaged 10,478 acres in farms in 1950, a reduction of 13.6 per cent from 1930. First tier townships averaged 14,064 acres, and the second tier averaged 17,079 per township. This was a decrease -120— of 4.8 per cent from 1930 for first tier townships, and 21.0 per cent for second tier townships. Cropland harvested showed a similar decline for the center town- ships, dr0pping 8.7 per cent from 1930 to 1950. Second tier town- ships, however, increased their cropland by 193 acres per township. By 1950, first tier townships averaged 41.2 per cent more crOpland per township than the center, and the second tier acreage was 71.5 per cent greater per township than the center townships. As previously stated, this tabulation presents a somewhat erroneous picture of farms and their acreages within the center and first tier townships. This results from the methods of the census in reporting farms. Farms that are located within urban territory are called urban farms, and are, therefore, not reported with the township within which they are located. In reporting on urban farms, only the county total is given. (The urban area within which these farms are located is not specified.) An adjustment of the averages per township in Table 16 should be made to show more accurately the changes that have_taken place within each of the township tiers -- center, first and second. . Table 17 presents farm data averages per township for each tier, adjusted to include urban farms within the counties in which there was a city mapped. The numbers and acreages in these farms are given above in footnote 17, page 117. Approximately 30 per cent of the total urban area is in the center townships, and about five per cent is in the second tier of townships. Almost the entire -121— Table 17 Adjusted Farm Averages Per Township, by Township Tier, A11 Mapped City Areasa -7 3 Center 3 First tier 3 Second tier Year : townships : townships : townships' and 3 Average 3 Average 3 Average 8 Average 3 Average 1 Average Item 3 per twp,: per farm: per twp.;4per farm: per twp.; per farm 1950 N0. farms 176 167 174 Acreages: Total 13,775 78.3 14,636 87.6 17,103 98.3 Cr0pped 6,863 40.0 7,671 45.9 8,989 51.7 Idle 5,194 29.5 2,315 13.9 1,263 7.3' 1940 No. farms 170 212 208 Acreages: Total 11,987 70.5 15,815 74.6 18,250 87.7 Cropped 5,854 34.4 8,175 38.6 9,004 43.3 Idle 773 4.5 1,175 5.5 1,220 5.9 1930 No. farms 168 169 183 Acreages: Total 12,469 74.2 14,835 87.8 17,422 95.2 Cropped 6,205 36.9 7,487 44.3 8,785 48.0 Idle 1,418 8.4 1,355 8.0 1,485 8.1 a Source: 1930, 1940, and 1950 United States Census 9: Agricultgre: Minor Civil D'vi io , Mighigan, United States Department of Commerce, Bureau of the Census, Washington, D. C. remaining 65 per cent of the total urban area is in the first tier townships. A similar division of these urban farms has been made -- 30 per cent of the total added to the center townships, 65 per cent added to the first tier townships, and 5 per cent added to the second tier townships. -122- With such a division of urban farms, the picture is changed some- what. Center townships average more farms than the first tier, which, in turn, had fewer farms than the second tier. Farm size grows progres- sively larger as the distance from the central city increases. Like- wise, the townships farther out average a larger acreage of cropland than those nearest the city. Rural Non-Farm Population Adjustments The enumeration of rural non-farm pOpulation is intended to include only those rural area people living outside of any city, town or village compact who carry on too little farming operations to be called farmers. However, the method of arriving at a listing of the rural non-farm population has resulted in the inclusion of a number of people that would be classified as urban in this study. All city suburb residents, living in unnamed suburbs of cities, are listed by the census as part of the pOpulation of the township in which they reside. When unin- corporated town and village, as well as farm, populations are sub- tracted from the township population to arrive at the rural non-farm pOpulation. these suburb residents become tabulated here as rural non-farm. Because of the impossibility of being able to distinguish in the census reports between suburb residents and those defined here as rural non-farm, the following method has been used to get a more accurate list- ing of rural non-farm p0pu1ation by township tiers. The results are given in Table 18. -123— Table 18 Study Area Rural Non-Farm Population Corrections By Township Tiers, 1950 Township :Census ruralepprox. sq. mi.xDensity perxAdjusted rural tier : non-fagma ; of zgr a1 areab ; 5g, mi. ; non-fatm Center 61,319 285 83.1c 23,684 First tier 500,034 3,037 59.8c 181,613 Second tier 262,686 7,195 36.5 262,686 "Other” 142,613 10,812 13.2 142,613 Total 966,652 21,329 28.6 610,596 a Source: 1250 United State§ Cenggg gtlpopulatiog, Characteristics gt thg o a i s Michi a , United States Department of Commerce, Bureau of the Census, Washington 25, D. C., Vol. II, Part 22. b Net of urban and all other non-farm land uses. c Estimated by applying second tier and "Other" township density dif- ferences to the center and first tier townships. For the mapped city areas, all the rural non-farm pOpulation in the center and first tier townships were deducted from the rural non-farm population for the study area. This leaves the rural non- farm in the second tier townships and all remaining study area townships (referred to here as "Other" townships). Rural non- farm population, in 1950, for the second tier was 262,686.18 There- fore, rural non-farm for "Other” townships is 142,613. There are approximately 7,195 square miles of rural land area in the second tier townships, and 10,812 square miles in the "Other" 18See also Appendix Table B. -124- townships.19 This ammounts to a rural non-farm density per square mile of 36.5 for the second tier, and 13.2 for the "Other" townships. The difference in density is 23.3 per square mile. Applying this figure to the differences between first and second tier densities results in a calculated density of 59.8 rural non-farm people per square mile for the first tier. A similar application to the dif- ference between center and first tier densities results in an es- timated rural non-farm p0pu1ation density of 83.1 per square mile for the center townships. Estimates of the total amount of rural land net of all non-farm land uses in the different tiers have been made. Multiplying the density per square mile by the total area in each tier results in an adjusted rural non-farm pOpulation for center townships of 23,684, and 181,613 for first tier townships. These corrected figures are believed to be much more accurate in specifying the number of people who live out in the open country not classified as farmers by the census. With these estimates, total rural non-farm population for the study area turns out to be 610,596, as compared with the 966,652 obtained by subtracting farm and village p0pu1ations from the totals given for the townships by the census. The difference between these two figures, of 356,056 would be an approximation of the number of people living in city suburbs whose numbers were entered by the census as part of the township population. 19Total township area corrected to account for small (correction line) townships, and non-farm acreages, leaving only rural area. -125- Estimated Rural Non-Farm Land Holdings No specific data are available which indicate the acreage held by rural non-farm residents. However, Moore's study of a segment of the Lansing area may be used as a basis for estimating such acreages. Moore's sample area was in two blocks, the Okemos area and the Williamston area.20 The Okemos area was approximately five to eight miles beyond the Lansing city limits, and the Williamston sample area averaged about 12 miles from Lansing. Urban influences in the Okemos sample area were found to be some- what stronger than in the Williamston sample. For this reason, the Williamston area results, rather than the total sample area, will be used here as being more nearly similar to what may exist in this study area. Moore found that in the Williamston sample rural non-farm resi- dences averaged 13 acres per holding. Of this, 26 per cent was idle 21 at the time of the survey. If we apply these findings to the ad- justed rural non-farm pOpulation of 610,596 for the study area, there is a possibility of more than 2,300,000 acres of land being held in rural non-farm residences.22 2OElon H. Moore, 9p. git., pp. ll, 12. 211618., pp. 64, 69. 22The 1950 census shows rural non-farm residences average 3.41 people per residence. For the study area this gives 179,060 rural non-farm residences if we use the adjusted rural non-farm population of 610,596. At 13 acres per rural non-farm residence, this amounts to a total of 2,327,780 acres in these holdings. "126- Such an estimate may be somewhat conservative, since the 1950 census for the state as a whole, lists 65,535 "places not counted as farms”, with a total of 2,461,703 acres in these places.23 These ”places” would be included within the rural non-farm p0pu1ation tabu- lation that has been made for the state. At 2.41 persons per rural non-farm residence,24 this accounts for only 223,474 rural non-farm residents, as compared with the 1,134,902 obtained here. If this total for the state is adjusted downward at the same rate as the study area, the corrected rural non-farm population for the state is 717,258. At 3.41 persons per rural non-farm household, the state had a total of 210,340 such residences in 1950, showing an enumeration by the census of less than one-third of the total rural non-farm residences in the state.25 This would seem to indicate that the census listing understates considerably the amount of land held by rural non-farm residents. If this is so, then the estimate made here may also understate the total amount of land in rural non-farm residences by quite a large acreage. This estimate amounts to a total of 2,734,420 acres in rural non-farm residences for the state, after adjusting rural 2312§Q_Qnttgg,§t§tg§,gggtug gt A ricul urea General Report, United States Department of Commerce, Bureau of the Census, Washington, D. C., Vol. II, 1952, pp. xxxii-xxxiii. 2412§Q,intgg,§t§tg§,Qgflgug 9t Population: Characteristics gt 1h3,292g1§tt9n, utghtggg, United States Department of Commerce, Bureau of the Census, Washington, D. C., Vol. II, Part 22, 1952, p. 55. 25This is primarily an elimination from enumeration by the census of places of three acres or more which had less than $150 value of products sold in 1940 and, therefore, does not intend to completely specify total acreages of land in rural non-farm holdings. -127- non-farm population for the state by the same percentage as the study area, and assuming that the rural non-farm residents in the remainder of the state held land at the same acreage per residence as that estimated for the study area. On the other hand, holdings in places not counted as farms may be largely in the areas of the state outside the study area. That part of the state may include a substantial number of holdings on which there were no farming Operations, or insufficient agricultural operations to qualify as farms. If this is a large number, with a large acreage of land per place, the attempt at a conservative es- timate may not have been achieved. From rural non-farm p0pu1ation totals for the entire state in each of the census years 1930 and 1950, presented in Chapter V, rural non-farm population has increased by 140.1 per cent from 1930 to 1950. Assuming that rural non-farm residence land holdings have not changed significantly over that period of time, there has been an increase of 1,466,501 acres in these residences since 1930. This is a rate of 73,325 acres going into rural non-farm residences annually. This, however, is not necessarily a net loss of land to agriculture, since Moore also found that 51 per cent of the land held by these people was leased out to farmers in the area. Assuming a similar propor- tion of land rented out by rural non-farm residents in the state, just less than one-half of this land annually going into rural non-farm residences has been lost to agriculture. However, there is likely nothing very permanent in this ”loss” of agricultural land. Changing -128- economic conditions could change the attitudes of land owners to either farming this land themselves, or renting out more of it to farmers, since only a very small part of the land holding may have been altered in such a way that it is no longer suitable for farming Operations. Idle land in rural non-farm holdings in Moore's study amounted to 26 per cent in the Williamston sample area. If we again use the Williamston area as a basis for an estimate, there is a possibility of a substantial acreage of land in rural non-farm holdings that is lying idle. Using the adjusted rural non-farm p0pu1ation estimate for the study area, and the state, the estimate of idle land in the study area is 605,223 acres. That for the state amounts to 710,949. acres. This approximation is in addition to the idle land in farms as enumerated by the census. Urban Acreage Potentials 0h further estimate for the study area in general will be made here. This is the potential land now ripening into urban uses -- a ripening process that could be expected to take ten to twenty years, or more. To make this estimate, the Lansing-East Lansing area is used as possibly typifying the study area as to the extent of land ripening into urban uses. -129- 26 are Acreage data from a previous study by Barlow and leberger used upon which to base a judgment of the extent to which urban pres- sures extend beyond the area here mapped as "developed". In that study, lands within Ingham county were classified into four groups: urban, urbanized, suburban, and rural./ All the land area within the corporate boundaries of cities were considered as ’ urban land. Urbanized land boundaries were drawn around Lansing and East Lansing from the urbanized area described in the 1950 census, . and including also the incorporated villages of the country. The boundaries of the suburban area were drawn with the aid of local real estate agents who were familiar with the area and the land transfers that were taking place. This area—type includes land that has a high potential for subdivision in the near future. It is land that now has a strong suburban influence, but which also includes a number of farms within its boundaries. Within this area, a large number of subdivisions have been laid out, including also many non~ platted residential pr0perties and land that has been sold or optioned for subdividing later. . The outer boundary of the suburban area covers considerably more land than that mapped in this study as the contiguous, developed suburb of Lansing and East Lansing. Comparisons of the two areas 26See Raleigh Barlowe and 0thmar Limberger, ”Relationship of Tax Assessed Valuations to the Sales Values of Real Properties, Ingham County, Michigan, 1950-53,” Quarterly Bulletig, Michigan Agricultural Experiment Station, Michigan State University, East Lansing, Vol. 39, No. 1, Aug., 1956, pp. 143-162. -130- ought to give some indication of the amount of land that is ripening into urban use in part of Ingham county with implications for the study area. It should be remembered that this "potential" area includes only’ Ingham county, excluding in that study the similar land area lying in \ Eaton and Clinton counties. For this reason, probably not more than two-thirds of the total potential land area surrounding Lansing and East Lansing is accounted for. Figure 15 shows the area outlined as suburban, or "potential" urban land, by Barlowe and Limberger. Also indicated is the land . area mapped in this study as ”developed” in this study. As mapped in this study, the developed area, including incorporated land, totals approximately 31,480 acres. The total area outlined by Barlowe and Limberger amounts to about 61,940 acres -- an additional 30,460 acres, which may be looked upon as having a high potential for urban use due to the high prOportion of real estate transfers in- tending this land to go into urban type developments. If the potential urban land in Ingham county approximates two-thirds of the total potential urban land around Lansing and East Lansing, this acreage may approach 50,000 acres for the entire area ringing these two cities. Such an acreage would be about 159 per cent of the total area mapped in this study as develOped urban land in the Lansing-East Lansing area. Although the Lansing-East Lansing area may not closely typify the amount of land that may soon ripen to urban use in the study area, -13l- fl = Incorporated Area fl = Developed Suburbs, 1940 = Developed Suburbs, 1955 = Potential Urban Land, 1955 :1 = Rural Land Scale: Three-eighths inch = one mile Figure 15. Corporate, Suburb, and Potential Urban Land Areas, Lansing and East Lansing, Michigan. —132- adjustments to allow for differences in rates of change may aid in indi- cating the extent of such land acreages. The rate of urban expansion in the Lansing-East Lansing area was approximately 25 per cent greater than that for the study area as a whole.27 Adjusting for this difference in the relative rates of urban growth, and given the assumptions above, the remainder of the study area may have had an expansion in its potential urban land of about 120 per cent (based on the 159 per cent greater area of the potential urban land over that mapped as developed in the Lansing-East Lansing area). If that is so, these remaining mapped cities may be surrounded by an area of nearly 750,000 acres of land that has been purchased for sub- division, or Optioned for that purpose. The total of such acreages for the study area would be, roughly, 850,000 acres, more than three-fourths of the total developed urban area existing in 1955 when these city areas were mapped, and more than two times the acreage platted be- tween 1940 and 1955. An estimate such as this cannot help but be highly speculative. Even if the acreage estimate is exactly accurate today, changing condi— tions may later cause this land to revert back to agricultural owner- ship and use. A considerable amount of this land classified as {potential has been purchased as a speculation but is still being 1 used as farmland. This estimate can approach accuracy, in direction if not in magnitude, only if the population growth of the study area 27See Table 5, p. 67. —133- continues, and if economic activity continues to make it possible for { large numbers of people to satisfy their desires for greater living space than the more compact city can offer. CHAPTER V AGRICULTURAL CHANGES IN THE STUDY AREA A grouping of townships different from that of the previous chapter has been made that seems also to indicate substantial effects of the non-fare population upon agriculture in the area of this study. In this grouping, all townships within the study area have been classified on the basis of the rural non-fare population as a per cent of the total population for 1950. Four groupings have been set up that classify townships (and counties) as “rural”, ”primarily rural“, ”primarily urban“, and "urban”. Those in which the rural non-farm population was 10 per cent or less of the total rural population were classified as rural; those from 10.1 per cent to 50 per cent, primarily rural, those from 50.1 per cent to 90 per cent, primarily urban; and those whose rural non-farm popula- tion was 90.1 per cent or more were lcassed as urban. In; tggnghtps. A simple tabulation of the townships in the various percentage group classifications is shown in Table 19. Changes in the number of townships within these groups is also shown for each of the three census years from 1930. . Only the rural group of townships has decreased in number over this period of time, being reduced by 81.5 per cent, with almost all of this decrease occurring after 1940. -135- Table 19 Number of Townships in Percentage Groupings of Townships, 1930, 1940 and 1950a Township 3 Percentage : Census Year : GrOUpb 3 1930 x 1940 8 1950 Rural 0 - 10 276 272 51 Primarily Rural 10.1 - 50 347 334 433 Primarily Urban 50.1 - 9O 69 85 184 Urban 90.1 - 100 17 18 41 a Source: L250 United States Censug gt P0pu1ation: Characterigticg gt tgg Population, Michigan, United States Department of Commerce, Bureau of the Census, Washington, D. C., Vol. II, Part 22, 1952. b Determined by calculating the rural non-farm p0pu1ation as a per cent of the total rural population for each township. The other three groups also show sizeable changes in numbers. Again, the majority of these shifts occurred after 1940. The urban group of townships.has increased by more than 140 per cent since 1930 while those classed as primarily urban increased by more than 165 per cent during that time. Primarily rural townships also showed an in- crease (24.8 per cent) between 1930 and 1950. Together, the rural and primarily rural townships made up 87.9 per cent of all townships in 1930. By 1950, their percentage had fallen to 68.3, with 25.9 and 5.8 per cent being made up of primarily urban and urban townships, respectively. Even though there was a certain amount of urbanization during the 1930's, it was not until World War II and the years following that -136— the process really gathered momentum. Here we have some evidence, at least from the standpoint of the growth in rural non-farm p0pu- 1ation, that "a home in the country" and the accompanying land-use changes were not of any great prOportions until after 1940. Table 20 presents information on average population and farm numbers per township within each of the percentage classifications. Table 20 P0pulation Categories and Farms in the Average Township, By Township Groups, 1950a Township :Number of : Population : Number Group :Townships : Total : RNF : Farm : of fgrms Rural 51 1,209 44 764 160 Primarily rural 433 1,418 329 782 169 Primarily urban 184 3,431 1,906 743 156 Urban 41 13,574 11,489 412 182 a Sources: 1950 United States Census gt P0pulation: Characteristicg gt the Population, Michigan, United States Department gt Commerce, Bureau of the Census, Washington, D. C., Vol. II, Part 22, 1952; and, 1950 United States Censgs gt Agricul- ture: Minor Civil Divisions, Michigan, United States Department of Commerce, Bureau of the Census, Washington, D. C. Those townships labelled rural had the smallest total population, affected primarily by the small number of the rural non-farm popula- tion. For each progressively more urbanized grouping, total as well as rural non-farm pOpulation increased considerably. Little difference in farm population per township exists, except for the urban townships. In this group, farm population averages only 412 per township. -137- Consistent differences in farm numbers are not evident between percentage groups. The rural townships average 160 farms per town- ship with the primarily rural townships averaging 169. Primarily urban townships, however, have fewer farms per township than either of these. On the other hand, urban townships show somewhat more farms than the other groupings, averaging 182 per township. Some evidence of the effect of the non-farm p0pu1ation upon agriculture is given in Table 21. Table 21 The Average Farm, by Township Groups, 19508 Township Group : Total : Acres of : Pet ge gt gt gtgglgagl lg Acre es ! Ctgglagd ; gta lug g flax: OIDEI* Idlg 1 Rural 124.4 76.7 50.2 21.7 18.8 9.3 Primarily rural 107.7 64.8 54.0 19.7 14.3 12.0 Primarily urban 91.8 54.3 52.4 20.2 13.1 14.3 Urban 54.2 30.7 44.7 19.2 17.8 17 6 ‘ Source: l2§0 Uglteg States Cen§u§ gt Agtiggltute: Mlno; Clvll inlslggg, Mlghlgan, United States Department of Commerce, Bureau of the Census, Washington, D. C. b Includes corn for all purposes, winter wheat, oats, barley and rye. c Includes all cropland from which hay was cut, and silage made from grass or hay crops. 9 All other farm crop production not specified in b and c. Acreages of land in farms consistently decrease as the non-farm p0pu1ation increases, ranging downward from an average of 124.4 acres per farm in the rural townships to 54.2 acres per farm in the urban townships. -138- CrOpland acreages are similarly affected. The rural township farms averaged 76.7 acres per farm, while those in the urban group averaged only 30.7 acres. Another difference here is the percentage of total farm acres ?‘ that is crOpland (including idle cropland). In the rural township 3 farms, crOpland averaged 61.7 per cent of total farm acres. Primarily 3 rural township farms averaged 60.2 per cent of their total acres in 3 cropland. For the primarily urban and urban township farms, this a proportion fell to 59.2 and 56.6 per cent, respectively. One of the reasons for this difference may be that as farms get smaller and smaller (as they do in the more urbanized townships), the amount of land in fence lines, lanes, waste and farmstead area be- comes proportionately larger. Only small differences exist in the percentages of cropland in grain1 2 and hay cr0ps. Roughly one-half of the cropland in the four groups was used for grain crops and about one-fifth for hay crops. Urban township farms used the smallest proportion of their cropland for grain crOps (44.7 per cent), while the primarily rural township farms had the largest prOportion with 54.0 per cent of their crOpland used to produce grain crops. A consistent difference in the scale from rural to urban town- ships was found in the prOportion of cropland that was left lying idle at the time of the census enumeration. Rural township farms left 9.3 per cent of their crOpland idle as compared with 12.0, 14.3, and 17.6 '139' per cent respectively for the primarily rural, primarily urban, and urban townships. Igg gougtieg. Further indications of the effects of urbanization on agriculture can be seen in tabulations of data at the county level. Counties have been classified on the same basis as were the townships, using the rural non-farm population percentage of total rural popula- tion as an indicator of the degree of urbanization in each of the counties. Statistical analyses of several pairs of variables have been made. the least-squares regression method with a two-variable equation of the form Yc = a + bX was used for describing the relationships be- tween these paired variables.3 In each case, the dependent variable Yc changes in value according to the variation in X, the independent variable. The coefficient of X (b) indicates the amount of this change in Yc, showing the number of units of change in Y6 that ac- companies each unit of change in X. The constant ”a” gives the Y axis intercept -- the value of Yc when X is zero. The standard error for each estimating equation (SY.X) is calcu- lated which measures the amount of divergence of the actual values of the dependent variable from their computed values. 3The method used is that described in F. E. Croxton and 0. J. Cowden, Applied General Statistics (2nd ed.), Prentice-Hall, Inc., Englewood Cliffs, 1955, pp. 451-469. '140‘ The coefficient of correlation is also calculated which indicates the degree of relationship between the variables.4 The square of the correlation coefficient (r2) permits a statement regarding the prOpor- tionate amount of variation in the dependent variable that has been explained by the estimating equation. Per cent rural non-farm: the independent variable. For two reasons, the per cent rural non-farm population was here taken to be quite accurate as an indicator of the degree of urbanization that has taken place at varying rates in the counties included in the study area; (1) As a number of the studies reviewed in Chapter 11 indicated, urban pressures within the corporate city were, to a large extent, responsible for the out-migration of people to the rural areas; and (2) Since rural non-farm residents are not farmers of any type they must be employed in urban areas (or have other urban, or non-farm, sources of income). The per cent rural non~farm population category was, therefore, expected to represent quite well the county differences in urban p0pu1ation, and the differences between counties in the pro- portion of the population employed in non-agricultural pursuits. The simple correlation analyses which were made were carried out under the assumption that per cent rural non-farm population could be used 4The test of significance for the ”r" value is made by the use of The F test table as given in F. A. Pearson and K. R. Bennett, Statis- tical Methods, John Wiley and Sons, Inc., New York, 1942, p. 412. Where +he rcrrelation coefficient is significant at the 95 per cent level it will be reported as significant; and if at the 99 per cent level, as highly significant. -l4l- as the independent variable with which variations in agriculture could be correlated. Tests of relationship are then expected to show how much of the variation in these agricultural characteristics are related to or associated with variations in the rural non- farm population. Figure 16 presents two tests using per cent rural non-farm population compared with average acres per farm and per cent of total farm in cropland.5 A close correlation for each pairing can be noted. For the effect of rural non-farm p0pu1ation on average farm size the regression equation is Y0 = 131.17 - .542X. The r2 of .264 indicates that 26.4 per cent of the variation of farm size between counties is associated with county-to-county varia- tion in rural non-farm population. The r value of -.514 is highly significant. The equation shows that as the rural non-farm per- centage increases by 10 percentage points the average size of farm will decrease by 5.42 acres.6 5Data for Figure 16 are presented in Appendix Tables D-1 and D-2. 6The danger of attempting to extrapolate inferences beyond the range of the data covered here (and in the following Figures, as well) should be noted. It may not be too unreasonable to expect average fern size to be 131.17 acres, as shown in the equation, when the percent of rural non-farm population is zero. But going in the other direction to a rural non-farm population of 100 per cent would give an average farm size of 76.97 acres -- an obvious impossibility. This may suggest the line of relationship is not linear as de- scribed in the equation, but that it is curvilinear. Average farm size does trend downward rather sharply at the highest rural non- farm population,percentages, as can beseen in Appendix D-l. ' a L‘fll—‘fl . ’142’ 150 100 ‘1' E (U E He m '3 Average Acres Per Farm ‘hl25,75 ;; ' ‘4 w H 0' m m 0 o la 3 a “ L) —_e Per Cent of Total Farm in Cropland 100,50 3 Q- — i '0 20* 40 60 80 100 Per Cent Rural Non-Farm Population Figure 16. Per Cent Rural Non-Farm Population Related to Average Acres Per Farm, and to Per Cent of Total Farmland Crapped The relationship between rural non-farm p0pu1ation and the per- centage of the total farm in cropland was found to be non-significant. The plotting of the regression equation does not differ greatly from a horizontal line (the coefficient, b, equalling only .083). A value of .062 for r2 indicates that only 6.2 per cent of the variation in the per cent of the farm in cropland is associated with variations in rural non-farm population. The r value of -.249 is somewhat be- low the .325 required for significance at the 95 per cent level. In Figure 17 are presented regression lines plotted to show the relationships between rural non-farm population and four other measures of agricultural land use.7 7Data for Figure 17 are presented in Appendix Tables D-3 through D'ée 75 ’143’ Grain Crops 50, Hay and Legumes 25 ( Cropland Idle / Per Cent of Total Cropland w--. ...._ i— .4 .e on. t. C a . —_i ___ ——* Other Crops 20 40 60 ’80 100 Per Cent Rural Non-Farm Population Figure 17. Per Cent Rural Non-Farm Population Related to Per Cent of Cropland in Grain Crops, Hay and Legumes, Other Crops, and Idle The statistical measures relating rural non-farm pOpulation and each land-use type, individually, are: gtof cropland in8 Regresgion eguation 5! x _t3 .2. grain crops Yc = 54.01 - .023X 8.33 .003 -.O56 hay and legumes Yc = 31.28 - .091X 6.97 .067 -.259 other crops Yc = 5.10 + .043X 6.05 .021 .143 idle Yc = 9.32 + .076X 4.61 .103 .321 The first three of these relationships show very little effect of the degree of urbanization on land-use patterns, yeilding equations with 8"Grain crOps' includes corn grown for all purposes, winter wheat, barley, oats and rye. "Hay and legumes” includes all land from which hay was cut, and beans and soybeans. "Other crops” includes spring wheat, buckwheat, flax, emmer and spelt, sugar beets, potatoes, popcorn, mint, all vegetable crops, berries, tree fruits and nuts. ‘144’ low b values and non-significant r values. The most significant, although still a non-significant, r value is that for idle land. In this, a relatively.1ow degree of association is shown with 10.3 per cent of the between-county variations in idle crOpland occurring with g, the county-to-county variations in per cent rural non-farm pOpulation. (1 With land in the more highly urbanized areas being considerably ( higher in price, one would expect that the individual farmer nearest 5, the urban center would make more intensive use of his land. However, i for at least some farmland owners, there may have been a strong feeling of expectation related to current land use versus future sale of the land which causes this apparent inversion of use-intensity. During this period, the area included in this study was undergoing an es- pecially rapid growth in urbanization with the result that land prices were rising rapidly in areas surrounding urban centers. A landowner near these centers may have been in a position to feel with consider- able certainty that ”next year someone will Offer an even higher price for this land.“ With such an attitude, ”today's” return compared with ”tomorrow's” anticipated return might be Of only minor considera- tion, relatively, and "not worth the effort” of carrying on agricultural Operations. Evidence that this could not have been a very widespread feeling is given by the low b value of only .076 -- an increase of 10 percentage points in rural non-farm population being accompanied by only 0.76 per cent increase in cropland left lying idle. 7145' In line with von Thfinen's location theory, one would have ex- pected to find the proportion of grain crops, hay and legumes, and quite sharply reduced, and a substantial increase in "other” crops (including truck-gardening and other more intensive land-use'crops) occurring along with increased urbanization. Since this does not occur, the relationships derived might appear to be at Odds with that theory. It must be recognized, however, that the conditional assump- tions laid down in that concept are not met in this study. Soils and tOpography are not perfectly uniform. The effect of distances from the market have been overcome to a large extent by greatly improved transportation, so that perishability and bulkiness are not such critical determinants of production location as in von Thfinen's time. Nor is this a study of a single market isolated from all others, and, therefore, able to be a single price-determining market. Because of technological improvements, markets are able to Ob- tain much Of the product of intensive land-use crops from areas of lesser seasonality of production. This reduces the necessity of re- lying upon local agriculture to intensify as demand develOps for truck gardening and the variety of other crops needed for the urban market. The result is, that, instead of having a narrowly confined zone of production for each type of crop, sources become scattered over extremely wide areas. No significant relationship can be noted between per cent rural non-farm population and the proportion of farms in pasture, or in the “146' intensity of grazing as expressed by the number of animal units9 per acre of pasture as shown in Figure 18.10 75.r.45 E E m “‘5O"'30 " Pasture F, H 3 fl 3 s “a E, 250 .15 H Animal Units Q (U U .5 3 E Q. 20 40 60 80 100 Per Cent Rural Non-Farm Population Figure 18. Per Cent Rural Non-Farm Population Related to Per Cent of Total Farm Pastured, and to Animal Units Per Acre of Pasture The regression equation relating rural non-farm population to per cent of the farm in pasture is YC = 26.77 - .032X. The SY.X = 4.77, r2 = .018 and r = .135. For rural non-farm and animal units per acre of pasture the estimating equation is Yc = .28 + .OO2X, 5Y.X = .078, r2 = .003 and r = .055. In both cases, the b value is little different from zero with a plot of the regression line being 9Animal unit conversion rates were taken from: Earn Management Fact§ gng Fi ures, Ag. Econ. 529, Agricultural Economics Department, COOperative Extension Service, Michigan State College, East Lansing, October 1953, Table 40, p. 67. 10Data for Figure 18 are presented in Appendix Tables D-7 and D-8. “14'7- ver nearly a horizontal line. Less than 2 per cent of the variation in per cent pasture land, and less than 8 per cent of the variation in animal units per acre of pasture are explained by these equations. Measures of much greater significance resulted when the per cent rural non-farm pOpulation was related, in turn, to the per cent of all farms less than 50 acres, and the per cent of all farms with less than $1,000 value of product. The lines of regression for these relationships are plotted in Figure 19, both with highly significant r values. 75. 50 Less than $1,000 25 Less than 50 acres Per Cent of All Farms 20 40 60 80 100 Rural Non-Faun Population Figure 19. Per Cent Rural Non-Farm Population Related to Per Cent of all Farms Less than 50 Acres, and Per Cent of all Farm With Less than $1,000 of Products Sold '148' The estimating equation for the relation between rural non-farm and farms of less than 50 acres is Yc = 9.88 + .417X, with SY.X = 8.57, r2 = .536 and r = .732. A substantial effect by the rural non-farm population on the prOportion of small farms is shown by this equa- tion, with 53.6 per cent of the variation between counties being associated with between-county variations in the rural non-farm pOpulation.11 In the test of relation between rural non-farm pOpulation and farms with less than $1,000 value of product, the estimating equation is v, = 15.15 + .382, sy,x = 7.76, r2 = .503 and r = .709. Here, too, a strong correlation is shown, with more than 50 per cent Of the between-county variation in the per cent of farms producing a very low value of output, being associated with a similar type variation in rural non-farm p0pu1ation. Part of the reason for the large number Of very small farms in the more highly urbanized counties with low value of output would seem to be clear. As more and more individuals seek residence out in the open country, these sites must come from existing farms (e.g., highway frontage sales by farmers for residential sites). As this movement continues, the average farm size in an urbanizing area must be reduced. The same effect must be exhibited in total production per farm. When it is recognized that farms do not intensify their Operations to any large degree as a result of the urbanizing process, smaller 11Data for Figure 19 are presented in Appendix Tables D-9 and D-lO. '149‘ farms, Operated on much the same pattern as befcre, cannot help in have a smaller volume of output to market. The line of regression plotted in Figure 20 describes the rela- tion found between per cent rural non-farm pOpulation and part~time farms as a per cent of all farms in each county.*2 The b value of .206 in the estimating equation (Y = 21.89 + .206X) indicates a c substantially greater prOportion of part-time farms associated with increased Urbanization. The standard error is 8.58, r2 = .194, with r = .440 being highly significant. 75 q 50. 25, 1 Per Cent of all Farms V v 0 20 40 60 80 100 Rural Non-Farm Population Figure 20. Per Cent Rural Non-Farm Population Related to Part-time Farms as a Per Cent of all Farms 12Data for Figure 20 are presented in Appendix Table D-ll. -150- One would not expect rural non-farm pOpulation to be directly re- lated to the increase in part-time farms, since a rural non-farm resi- dent by definition is not a farmer. But, by their very presence, they must cause many farms to be reduced in size by each buying up a small part of a farm. Formerly full-time farmers might then find themselves in a position of having to supplement their farm income with off-farm employment. The test of relationship between rural non-farm population and the per cent Of all farmland rented out yielded the estimating equa- tion Y, = 32.24 - .125x, with s,“x = 5.36, r2 = .85, and a highly significant r value of -.430. The plot of this equation is shown in 13 Figure 21. '2 so) 2 E (U U: T; ¥ ,, 25, O p 1.. C 8 H 0.) Q. 0 20 40 65 80 100 Rural Non-Farm Population Figure 21. Per Cent Rural Non-Farm Population Related to Fanmland That is Rented Out as a Per Cent of all Farmland 13Data for Figure 21 are presented in Appendix Table D-l2. “151' The proportion of all farmland rented out approximates one-third in the most rural counties, generally declining as the counties become more urbanized. The rate of this decline is indicated by the b value of -.125. Such a declining relationship is likely the result of the number of people who buy up farms, or parts of farms, to Operate on a part- time basis or even a hobby farm basis. As the number of these types of farms increases, the remaining farmland available for rent must decline as a per cent of the total. Too, with stronger demand for land by non-farm people in the more highly urbanized counties, the sales market would likely attract a certain amount of land that might otherwise be offered for rent. CHAPTER VI SUMMARY AND CONCLUSIONS Summary Many pe0p1e have been concerned with the problems caused by popu- lation growth and movement. Those whose interests center around the rural territory have pointed their studies toward particular problem areas in the rural community. As urban people move out of the more crowded city, a fringe area develOps with problems unique to itself. A number of studies have devoted their attention to these areas and to methods that may be helpful in solving their particular problems.1 Urban oriented studies have often condemned the patterns of urban development that result from complete individual freedom in the plat- ting of land for urban use. Unregulated, haphazard suburb plattings many times have resulted in failure to provide the kinds of services that could have been obtained from the apprOpriated land resources. A number of these studies have been critical of speculation and premature subdivision as this has resulted in losses of investors funds and a com- plete waste of large areas of land. Communities also lose when their tax bases are reduced as large blocs of land become tax delinquent and fail to contribute to the maintenance of community services. 1There is a large number of such problems that result from the urbanization of rural land. These deal with the local social and civil problems that arise as an area becomes increasingly more densely p0pu1ated. Such problems are outside the realm of this study. These would be of much concern to farm pe0p1e especially when they are caught up in the problems of local government and financing for schools, roads and many other urban-type public service needs that increase with population. ~15;~ This treatise has attempted to point out some of the effeits of the urbanization process Upon agricultd:e. Data post which to base these indicators were taken from the United States population and agricultural censuses for 1930, 1940 and 1950. In order to gain some further insight into the land that has ripened into urban use, cities of over 15,000 population were mapped in a way which shows the extreme outer boundary of the built-up city and suburban area. With known urban acreages as of two given points in time (1940 and 1955), the trend in urban acreage expansion can at least be estimated if not closely specified. A certain amount of census data available at the township level permitted an analysis of the effect of the degree of urbanization upon agriculture in the townships. The rural non-farm population as a per cent of the total population was taken as an index of the degree of urbanization. Several tests of relationship using census data at the county level were made, using the least-squares regression technique as the mechanical means of determining the closeness of the relationship for paired vari— ables. Conclusions Urban expansion. The state of Michigan has experienced a rapid growth in its urban population which occurred most rapidly following the impetus to industrial expansion required to meet war-product needs -154- during the 1940's. With the return to productioa far civiliaa needs, the expansion of indistrial output continued at a high ra=e aid attracted many additional workers. With the majority of the industrial capacity located in the southern part of the state, this area 510 experienced the greatest increase in population. Hensit is that the expansion of urban land has been the most rapid and striking. For the study area as a whole, the acreage that has gone into urban use is quite large. Of greater significance, however, is the fact that more than one-third of the total urban land mapped had ripened into urban use after 1940. The total incorporated urban land in the study area amounted to 583,900 acres in 1940. By that time an addi- tional 84,820 acres had been subdivided and platted outside the incorporated area. By 1955, the total of incorporated urban and platted suburb land had grown to 1,057,600 acres. This 388,880 acres of new urban land represents an annual rate of 25,925 acres going out of agriculture into urban use. This is only part of the total acreage of ripening land. As urban populations grow, additional needs develOp for highways and im- proved areas for recreational use outside of the city. In addition to this there is a land use related to urbanization where rural land acreages are in the hands of non-farming people. The rural non-farm population represehts a rapidly growing segment of the total population. From 1930 to 1940, the rural non-farm popu- lation increased by 40.8 per cent. The increase in the next ten-year -155— period was more than twice as great, amounting to 91.79 Per cent. In Chapter IV, an estimate of the total acreage held by rural non-farm residents was made. Admittedly only an approximation, this may accant to more than 2,300,000 acres. If the average acres per rural non-farm residence holding has not changed significantly since 1940, the annual appropriation for this purpose may approach 100,000 acres for the study area. Future urban land expansion can be expected to continue if popu1a~ tion growth and economdc activity is maintained. Measures of past changes in urban acreages reflect the stimulation of these two factors. Their continuation would result in approximately 125,000 acres per year going into urban and rural non-farm land uses. In addition to these uses are the public appropriations of land. Recreation land use increases, as represented by parks and recreation areas, have shown considerable growth in recent years. Of the 7,118 acres in state parks within the study area, only 312 acres have been added to the system since 1940. But for the state as a whole there are 114,163 acres in this type of use, of which 77,471 acres have been added since 1940. On the other hand there were in the study area, in 1955, a total of 60,905 acres in state recreation areas, all of which have been added since 1940. This represents an annual rate of 4,060 acres going into this use. Such appropriations of land for public enjoyment can be ex- pected to continue as the population grows, and as leisure and recreation become more important uses of a person's time. -156- Public highway and road construction programs can also be expected to take considerable acreages of land in the future. In 1959, there were reported to be 853,000 acres in highways, county roads and railroad 2 By 1955, this acreage had rights-of-way in the state of Michigan. grown to 861,312 acres, even though there had been some amount of right- of-way abandonment by the railroads in the northern part of the state. For this five-year period, 1,662 net additional acres had been taken for transportation use annually. The current highway building program is at a much more rapid rate. Nawhighway locations and widening projects are expected to take another 50,000 acres by about 1962. Over this twelve-year span of time the average appropriation amounts to about 4,850 acres per year. A rough estimate of the total land ripening to non-agricultural uses annually would be somewhere in the neighborhood of 135,000 acres. Can we expect this to continue on for a very long period of time? The answer to this question is in the affirmative, provided; (1) the growth in population continues; (2) industrial expansion continues which provides jobs for these greater numbers of people; (3) economic activity remains at a relatively high level, with incomes also averaging high enough that the land holding desires of many can be satisfied; and (4) that people's desires do not change and alter the present pattern of preferences, including their support of public development of land acre- ages along many lines. 2United States Department of Agriculture, Basic Land Use Statistics, 1950, Supplement to “Major Uses of Land in the United States", Technical Bulletin 1082, United States Department of Agriculture, Bureau of Agri- cultural Economics, Washington, D. C., September, 1953, p. 33. -157- It is possible that a sharp downturn in the economy may halt or re- verse the current p0pu1ation movement. But even during the extended depression of the 1930‘s, the rural non-farm population incrcased (from 1930 to 1940) by a little over 40 per cent. Whether all this increase occurred near the end of that ten-year period, or over the en_ tire period is not known. Most likely it extended over most of that time. If that is so, even an extended depression probably would halt the movement only for a relatively short period of time. Changes in agrigulture, Measures of the degree of urbanizationis effect upon agriculture in the study area are implied by changes in farming that have taken place. In the tiers of townships surrounding the mapped cities, effects of some importance were noted. The nearer the township to the central city, the greater was the reduction in farm numbers from 1930 to 1950. The inner townships also experienced the greatest loss in total farm acres, and in total acres of cropland harvested. A reverse relationship was found with respect to idle land that is difficult to explain. Instead of finding a reduction in the amount of idle cropland in farms nearer the city, the idle acreage increased. One possible explanation is that the expected net.return from farming the land, relative to the expected increase in salve value over a short period of time, was too small to encourage fuller use of that land. Further analyses were made that attempted to more directly specify the effect of urbanization upon farms, and the way in which crop and -l58- livestock production patterns might change as an area be;omes mot: urban» ized. Counties were classified and arrayed according to tteir rural rare farm population as a percentage of the total population. Witt this scaling of counties, tests of relationship were made using per cent rural nonwfarm population and the proportions of different crops as these varied by county. Instead of measuring such changes as might have occurred in each county over time, from 1930 to 1950, this method makes a "point-in—time" analysis using 1950 data only. From this it was reasoned that the relationships found could be expected to occur as a county becomes more and more urbanized through time. Some of the tests of relationships between per cent rural nonm farm population and county-to—county land use variations showed highly significant results. The more highly urbanized the county, the greater the effect. Table 22 presents a summary of the relationships that were tested. These relationships show how each of the related items increased or decreased as the rural non-farm population increased —- not as the rural non-farm population grew over time, for any one county, but on the basis of between-county variations in the rural non-farm populam tion. ”159- Table 22 Summary of Regression Equations Describing ReLationships Between Rural Non-Farm Population and Study Area Farms.9 1950 --:====:== Rural non-farm population Regression - related to equation Y.X r‘ _ r Average acres per farm Yc=l3l.l7-.542X 18.48 .264 -.5i4** % of farm in cropland YCS 56.01-.083X 6.64 .062 -0249 % of cropland in grain craps YO: 54.01-.023X 8.33 .003 -.056 hay and legumes YCI 31.28-.091X 6.97 .067 @0259 other crops Ye: 5.10+.043X 6.05 .021 .143 idle Yo: 9.326.076X 4.61 .103 .321* % of farm pastured Yc= 26.77-.032X 4.77 .018 .135 Animal units/acre pasture y.= .28+.002x 0.08 0003 .055 % of farms less than 50 acres Yo: 9.88+.4l7x 8.57 .536 .732** % of farms producing less than $1000 value of output Yc= 15.15-.382X 7.76 .503 .709** % part-time farms Yc- 21.89+.206X 8.58 .194 .440** % of farmland rented out Yc= 32.24-.125X 5.36 .185 -.430** * significant at the 95 per cent level. **significant at the 99 per cent level. The most highly significant relationships were found between rural non-farm population and the number of farms less than 50 acres as a per cent of all farms, and rural non-farm population and number of farms producing less than $1,000 value product as a per cent of all farms. Part-time farms as a per cent of all farms, and land rented out as a per cent of all farmland also showed significant relationships to rural non-farm population percentages, as did average farm size. Livestock grazing intensities as indicated by animal units per acre of pasture, and per cent of total farmland pastured showed the least effects from rural non-farm population variations. The category «150- of "other crOps" (which includes truck and garden ;:eps) arse ~ig~ w little effect from nearness to the urban centers. Apparently technical improvements in production and *r Janorzshion that have taken place in this area have reduced the locations; as“.s.ages that may have existed in years past. Nearness to the central city market does not appear to offer a large enough transportation differs ential to make it more profitable for nearby farms to raise marketm produce as compared with those farms further away. That there was an impact upon agriculture as a result of urbanizam tion is shown by the data. But to specify the degree of this impart is very difficult if not impossible. The appropriation of well over l.000,000 acres from 1940 to l955 for urban and urban-related uses must have come primarily from study area farms. Such a loss would have made its mark upon the farms in the area. However. all of this land was not taken from farms. During the period from 1940 to 1950, total acres in study area farms were reduced by 641,337 acres. It is possible that a somewhat larger acres age than this was sold for urban purposes9 with the balance being made up by bringing additional land into farms. During this same period of time, total crOpland increased by 90,371 acres. Here, also. is the possibility that new lands were brought, not only into farms, but into production even while large acreages were finding their way into none farm uses. Non-tillable land that ripened into urban uses would not necessarily reduce current production on farms. But there was also a substantial -l6l- acreage of "good" farmland that ripened, and this would result in fewer crop acres.3 To offset this loss, farmers have had to reclaim, through brush clearing and drainage, land that was previously non—tilled land. If this was a substitution of land more difficult and costly to till, for the land previously cropped, there has likely been an increase in the cost of carrying on farming operations. Here is one type of im- pact that cannot be measured because of the kind of data used in this study. A very rough estimate may be made be determining how much value product study area farmers "gave up" in disposing of their land to urban uses. Michigan farm-account summaries for 1954 show a gross income per acre of $65 for study area farms.4 If this becomes our measure of impact, study area farmers could have produced in the neigh- borhood of another $75,000,000 gross value output per year. 3At the time the cities were mapped, an attempt was made to obm serve Whether there had been any selectivity (with respect to land quality) of the land taken up for urban uses. There was no obvious attempt by developers to select either the "good" or "poor" land for urban use. Apparently the geographic location of the land was of much greater importance than land quality, with at least one exception. This is where hilly land has a particular appeal for a more exclusive type of development. Such land, in some areas, was chosen over more level land even though it may have been further away from the urban center. 4John C. Doneth, and others, Farming Today, Cooperative Extension Service, Department of Agricultural Economics, Michigan State College, East Lansing, A. E0. 538, Areas 1 through 8, 1954. _~:fi .- -162— Some qualifications to this must be stated. If this ripened land had been kept in farms, study area farmers would also have had to dem velop the additional acreages of tillable land as they did from 1940 to 1950. It this had been done, what would have been the effect upon product prices? Theoretically, the increased output would sell at lower prices, and the value product given up would be less than that estimated above. How much less would depend upon the position of these farmers in the total market. The effect for most farm commodi- ties would likely be small, or even unnoticeable. For some others, however, Michigan production may make up a larger percentage of the total market, and there would be a noticeable reduction in market prices - given other things remaining unchanged. £232 2: the futurez Estimates of future urban and urban-related land use acreages, in themselves, do not tell much. It is important to know how much land may go into these uses. More important is where that land will come from and what its effects will be. If the rate of movement of land into non-farm uses through the years from 1940 to 1955 is maintained over the following twenty years, it is possible that another 2,750,000 acres may ripen to urban and public land uses. If the rural non-farm residential acreages are correctly estimated, and their relative proportion to the total is not changed, somewhere near 75 per cent of this acreage would likely go into rural non-farm holdings. A further question relates to the source of this land for expansion of non-agricultural uses. Out of the total of 15,505,740 acres in the -163- study area, 11,933,960 acres were in farms, and 1,875,716 acres were in non-farm uses as of 1950. This leaves an area of 1,696,064 acres which could be taken up for urban and related purposes without altering existing farms. But it is quite probable that only a very few of these acres are located near the urban centers. If this is so, future expansion would have to come at the expense of total farm acres. If the estimated future urban and urban-related acreage all comes out of today's farmland, this will leave less than 10,000,000 acres in study area farms -— a reduction of about 16 per cent. Will this loss reduce the productive ability of study area farms by the same amount? This would depend upon many things. Moore found that, for his total sample, 46 per cent of the land in rural non-farm residences was rented out to farmers.5 This would re_ duce the amount of land "lost“ to agriculture by about 1,000,000 acres, leaving nearly 11,000,000 acres in study area farms. Suppose the re- mainder to be lost. Study area farmers could still increase their productive acreage by much more than this if econondc conditions furno ish the incentive. These farms in 1950 had over 5,500,000 acres that were not cropland. Certainly some of this would be expensive to improve and produce agricultural products from, but a large part of it could be brought into production. 5Elon H. Moore, pp. £33,, pps. 64, 71-73. Moore conducted his survey during the period of the K0rean crisis. The pressures of in- creased military demand for agricultural products may have influenced farmers to seek additional land from rural residents. In such case, this may not be a "normal" pattern of land rentals. -164- Qg£_threatened.jgggwggpply._ Some people are greatly concerned over the possible seriousness incident to the urban appropriation of agricul- tural land. They see in this a growing momentum in the rate of land ripening to non-farm uses which keeps eating away at our food produc- base. Therefore, we must eventually reach a position at which our supply of land will be unable to furnish foods in the amounts needed. Is this an ill-founded concern? The growth of our national population over the last one and one-half decades has been quite large. One forecast points to a population total for the United States of 200,000,000 to 225,000,000 by 1975.6 Certainly we need not expect it to stay there. But how much higher will the total go before it levels off -— supposing that it will do that eventually? Here is one factor, when coupled with the loss of agricultural land to urbanization, that for many, adds up to a serious threat to our future food supply. If the population continues to increase, where will the necessary food come from? Such a threat may or may not be a real problem. Diminishing returns in agriculture certainly would prevent any multiplying of the output that might be attempted in meeting the needs of a multiplying population. But, over time, we are not dealing with diminishing returns to a particular production process which increases the application of a set of homogeneous variable inputs to a set of , 6United States Department of Agriculture, Agricultural Outlook Charts, 1955, Agricultural Marketing Service and Agricultural Research Service, United States Department of Agriculture, Washington, D. C., October, 1954, p. 2. ' -165- fixed inputs. The inputs used, both variable and fixed, are changed, not only in quantity by quality as well over time. Improved crop varieties, higher grade, more productive livestock, and better manage- ment practices in the use of an increasing number of "output boosters" ought to be forthcoming in the future. When we think of diminishing returns over time, then we must be concerned with secularly diminish- ing returns, and this is a great deal more difficult to specify. The production process of the future can only be estimated, as we are only estimating what the future p0pu1ation will be. Why, then, should we ascribe any more accuracy to one estimate than to the other? Past population growth is little more an accurate index with which to preo dict the population of many years hence than is the past growth in agricultural production an accurate indicator of future production rates. These estimates can be used as guides only. So far, our agricultural plant has been more than able to keep pace with pOpulation growth. Why should it not keep pace in the future? Given a constant level of technolOgy, future land losses would re- sult in a reduCtion of output in the study area farms. But a shrinking land base alone is a very poor measure of productive capacity because technologies do change. Without considering any changes other than land acres used, study area farmers still have the ability to make substantial adjustments in their use of farmland. In 1950, these farmers were using a little over one-half of their total farmland for crop production, with an additional 889,404 acres left lying idle. If market conditions demanded, this land -166- could be brought into production without too much difficulty. Also, some fraction of the non-tillable land in farms could likely be brought into production, but at a higher cost. In addition to these output sources is the possibility of more intensive use of existing cropland acreages. These could all add up to a very large increase in food out- put using today's level of technology. Welfare implications. What we do to our land base can aggravate any food supply problems that may develop in the future. It would not be unreasonable to assume that the majority of the increased population that can be looked for in the near future will locate in new suburb develOpments surrounding the cities. Some of these will also settle in the rural area. Our land base is a perpetual resource that can be maintained or destroyed - destroyed entirely or a little bit at a time. Whatever the result, there will be an influence on future generations. This is a resource base whose use is a long-term consideration, and our actions today should attempt to evaluate at least some of the longer-term im— pacts. 0n the question of appropriating land for urban-type uses, society may soon be called upon to make decisions as to whether this should be more carefully regulated. Under our present market system, individuals are free to determine which lands they will appropriate for non—farm uses. Where non-farm uses can outbid agriculture for the use of land, these uses must be higher from the standpoint of private costs and returns. Private costs and -l67- returns, on balance, may indicate that the individual is mathiging his satisfactions in taking agricultural land for residential or other urban-type uses. But what of other costs to society that the individual cannot consider? Where the individual is free to select the best agricultural land near the city for residential develOpment, farmers must substitute a poorer quality of land for it. A given agricultural output must be. obtained at a higher cost as a result of individual freedom in site. selection. Another type of social cost resulting from cemplete individual free- dom in taking land for urban use may be indicated by the waste of re- sources in "over—development". Renne has stated this was a common phenomena following World War I. In the 1920's there was estimated to be enough land subdivided to house another 18 million people.7 Indi- vidual freedom to choose (and to misjudge) resulted in much land idled and large investments lost, some for periods extending up to the resi- dential building boom following World War II. Firey brought up another problem that had serious social consequences. This was the springing up of blighted areas, both rural and urban, as a result of a complete lack of control.8 A number of township supervisors ZRoland R. Renne, Land Economics, Harper and Brothers, New York, 1947, n. 15, p. 425. 8Walter Firey, Social Aspects to Land Use Planning in the Country- City Fringe: The Case 9; Flint, Michigan, Michigan Agricultural Experi- ment Station Special Bulletin 339, East Lansing, June, 1946, pp. 19-25. -l68- contacted at the time cities were mapped for this study also brought this out as a problem requiring local government action. One township in the Bay City - Saginaw area had this problem thrust upon it as tar- paper shacks sprang up very rapidly throughout the rural area, which later caused tax delinquency problems. Public action for guidance. Regulatory action which "directs" urban and other developments assumes some set of goals important enough to make individual desires along these lines subordinate to the interests of the society. It also implies that we can specify today what is the best use tomorrow of a parcel of land. Are we.ablef to so judge, if that requires control now to assure certain land will be available at some future date? If the individual had difficulty in determining the best use of land within the framework of his personal criteria, how can we expect to predict with any accuracy what the wel~ fare changes for a large number of people might be as a result of land use regulation? Control over general types of land uses could have several goals, each of them of some importance to society. To this writer, the least justifiable of all is the "saving" goal -- preventing urban type uses of the good land so that land may be kept in agricultural production. If technological improvements in agriculture follow population growth, this saving of land would be simply a waste of effort - effort that could have been better diverted to more productive channels. -169- In terms of the total physical supply of land, urban land use will likely be only a very small proportion. From the standpoint of national food needs, reserving agricultural lands in Michigan can hardly be ex- pected to make a very great difference. Given the possibility that technology does fall behind population growth, actions to control urban uses would not have saved very many acres percentagewise. About all it can expect to do is postpone the day of reckoning when the supply of agricultural land is insufficient to produce the necessary food and fiber. What is the value of such a ”parole" in the life of a society -— a parole only, because the problem would still be there. The solution to the food supply problem lies in a growth of tech- nolOgy which approximates that of the population. But since we have no assurances that such will be the case, some degree of prudence could be exercised in the way our land as a resource base is expended. Looked at in this light, there may be some cause for concern. This would be so, especially, if current action could preserve the resource base and thereby have our needs met in the future as a result of that action. Of greater importance as a goal in the reservation of agricultural lands is that of minimizing the cost of producing the needed food and fiber at any point in time. Allowing the better grade lands to be ap- propriated for urban uses (and leaving the poorer grades to agriculture) will increase the cost to society of obtaining its food supply. Here is a problem worth considering in connection with land use regulation. There are savings in the costs to society that can be achieved by re- serving the good agricultural lands. This should furnish more of an ~170- incentive than attempting to justify the regulation of the various uses of land on the basis of urbanization's threat to the future food supply. Another goal of regulation includes the orderly development of urban areas. Urban communities have generally accepted as a necessity such regulations as building codes, rules for street layout, building set-back, zoning by type of urban use, etc. These regulatory practices are intended to make for more efficient utilization of land and conform~ ity with already developed areas. In the rural area, zoning of land uses has been applied in a number of different regions. Rural zoning may be applied to prevent low—quality residences from being built which may have a high probability of leading to slum conditions. Zoning may also be applied to regulate the type of agricultural use to which certain lands may be put. These forms of regulation over land use have had some application over a long period of years. Suggestions jg; further research._ This study has been hampered by a lack of data available at the township level. Especially because of this shortage of data, the objective of determining the impact of part- time farming upon agriculture in the study area has not been met very adequately. A more specific assessment of the impact of urbanization upon study area farms would have been possible had cost data for these farms been available. The general impact is shown in the way study area farms have adjusted in the face of the conditions within which they operated. -l7l- Such a study would require a survey to be made at the farm level for samples of farms which would analyze the costs and returns from farming. Sample areas would need to be selected according to various non-farm population densities within these sample areas. Classification of these areas could be done quite satisfactorily by using the same basis as was used in this study. Differences in costs and returns could then be attributed to the relative degrees of urbanization for each of the different areas, with the measure of impact being the net income of the samples of farms. A further question of importance is the land that is held by rural non-farm residents. This type of land use could be determined by much fuller access to census work-sheets. It could also be determined by a sampling method such as that used by Moore, but including many more sample areas. A very careful selection of sample areas would have to be made in order that the areas selected would be quite accurately representative of the total area. Either of the above methods could then furnish answers to important questions about the land in residential holdings. How this land is held carries an implication of some importance to the potential output of Michigan agriculture. The pattern of land ownership will determine to a large extent, whether it will be usable land or remain idle. Many small, fragmented holdings, each fenced in by itself, would make it difficult and unattractive to a farm operator who may wish to increase the size of his farm by renting nearby parcels of land. -l72— The additional information obtained in such studies as suggested above could add considerably to the knowledge regarding the effects of urbanization upon Michigan agriculture. -l73- BIBLIOGRAPHY Anderson, W. A., Fringe Families and Their Social Participation, Cornell University Agricultural Experiment Station Bulletin 909, Ithaca, April, 1955. Andrews, Richard 8., "Elements in the Urban-Fringe Pattern," The Journal 3: Land and Public Utility Economics, Vol. 18, No. 2, May, 1942. Andrews, Richard 8., "Urban Fringe Studies of Two Wisconsin Cities: A Summary,“ The Journal of Land and Public Utility Economics, Vol. 21, No. 4, November, 1945. Arnold, J. H. ., and F. Montgomery, Influence of a City_ on Fm ming, United States Department of Agriculture Bulletin 678, United States Govern~ ment Printing Office, Washington, D. C., 1918. Arpke, Fredrick, ”Land Use Control in the Urban Fringe of Portland, Oregon," Journal of Land and Public Utility Economics, Vol.18, No. 4, November, 1942. Barlowe, Raleigh, and 0thmar Limberger, ”Relationship of Tax Assessed Valuations to the Sales Vlaues of Real Pr0perties, Ingham County, Michigan, 1950-53,“ Quarterly Bulletin, Michigan Agricultural Experi— ment Station, Michigan State University, East Lansing, Vol. 39, No. 1, August, 1956. Beegle, J. Allen, “Characteristics of Michigan's Fringe Population,“ Rural Sociology, Vol. 12, No. 3, September, 1947. Beegle, J. Allen, Social Organization in the North Lansing Fringe, Mich- igan Agricultural Experiment Station Technical Bulletin 251, East Lansing, September, 1955. Black, John D., 'Coming Readjustments in Agriculture - Domestic Phases,“ Journal 21 Farm Economics, Vol. 31, No. 1, part 1, February, 1947. Black, John D., Bushrod Allin, and Charles C. Colby, “The Soil and the Sidewalk,” American Planning and Civic Annual, Rural Sociology, V01. 18, No. 2, June, 1953, p. 118. Blizzard, Samuel W., "The Social Significance of the Rural~Urban Fringe," Rural Sociology, V01. 18, N0. 2, June, 1953, p. 118. Blizzard, Samuel W., and W. F. Anderson 11, Problems in Rural-Urban Fringe Research: Conceptualization and Delineation, Pennsylvania Agricultural Experiment Station Progress Report No. 89, State College, 1952. -l74— Bromage, A. W., and J. A. Perkins, ”Willow Run Produces Bambers and Inter-Governmental Problems," The American Political Science Review, Vol. 36, No. 4 August, 1942. Conklin, Howard E., "The Rural-Urban Economy of the Elmira-Corning Region, ' The Journal of Land and Public Utility Economics, Vol.20, No. 1, February, 1944. Croxton, F. E., and D. J. Cowden, Applied General Statistics, (2nd ed.), Prentice-Hall, Inc., Englewood Cliffs, 1955. Dewey, Richard, "Peripheral Expansion in Milwaukee County,” The American Journal pf Sociology, Vol. 54, No. 2, September, 1948. Diehl, L. F., 'Major ASpects of Urbanization in the Philadelphia Metros politan Area,‘ The Journal of Land and Public Utility Economics, Vol. 19, No. 3, August, 1943. Enehl, L. F., ”Problems of Suburbia,“ Land Policy Review, Vol. 4, No. 8, August, 1941. Doneth, John C., and others, Farmigngodgy, Cooperative Extension Service, Department of Agricultural Economics, Michigan State College, East Lansing, A. EC. 538, Economic Areas 1, 2, 3, 4, 5, 6, 7 and 8, 1954. Ely, Richard T., and George S. Wehrwein, Land Economics, The Macmillan Company, New York, 1940. Fellman, J. E., "Urban Geographic Concepts at the Elementary and Secondary Levels," The Journal 3: Geography, Vol. 56, No. 6, September, 1957. Firey, Walter, “Ecological Considerations in Planning for Rural-Urban Fringes,” American Sociological Review, Vol. 11, No. 4, August, 1946. Firey, Walter, Social ASpects to Land Use Plannigg in the Country~City Fr ringe, Michigan Agricultural Experiment Station Special Bulletin 339, East Lansing, June, 1946. Funk, W. C., Value of a Small Plot of Ground to a LaboringpMan, United States Department of Agriculture Bulletin 602, United State Govern: ment Printing Office, Washington, D. C., 1918. Gibson, W. L., Jr., and 5. Bell, Jr., Land Utilization in Henrprounty, Virginia Agricultural Experiment Station Technical Bulletin 93, Blacksburg, 1944. Gist, Noel P., 'Ecological Decentralization and Rural-Urban Relationships," Rural Sociology, Vol. 17, No. 4, December, 1952. -175- Greeley, Roland 8., "Recreational Land Use in New England," Economic Geography, Vol. 18, No. 2, April, 1942. Hood, Kenneth, An Economic Study of Part-Time Farming in the Elmira and Albany Areas of New York, 1932 and 1933, Cornell Agricultural EXperia ment Station Bulletin 647, Ithaca, 1936. Hoover, Edgar M., Jr., Location Theory and the Shoe and Leather Industries, Harvard University Press, Cambridge, 1937. Lee, A. T. H., and J. E. Hauck, “Excessive Land Subdivision in the New Jersey Pine Area,“ The Journal 2: Land and Public Utility Economics, .Vol. 19, No. 2, May, 1943. McCain, W. C., Jr., and R. G. Burnright, ”The Social Significance of the Rural-Urban Fringe: From the Rural Point of View,” Rural Sociology, Vol. 18, No. 2, June, 1953. Melamid, A., "Geography and Planning: An Example from Cleveland, Ohio," The Journal 2: Geography, Vol. 56, No. 4, April, 1957. Michigan Department of Conservation, County Ma s, Lansing, 1955. Michigan State Highway Department, General Highway Maps, Lansing, 1940. Michigan State Highway Department, State Trunkline Mileages - Rural, Lansing, l955. Michigan State Highway Department, Third Annual Progress Report, County Road Commissions, Lansing, December, 1954. Moore, Elon H., and Raleigh Barlowe, Effects of Suburbanization on Rural Land Use, Michigan Agricultural Experiment Station Technical Bulletin 253, East Lansing, September, 1955. Selected Segment of the Lansing Rural-Urban Fringe, Unpublished Ph. D. Thesis, Michigan State University, East Lansing, 1953. Nielson, James, and others, Farm Management Facts and Figures, Agricul- tural Economics Department, COOperative Extension Service, Michigan State College, East Lansing, Ag. Econ. 529, October, 1953. Pearson, F. A., and K. R. Bennett, Statistical Methods, John Wiley and Sons, Inc., New York, 1942. Perkins, J. A., ”The Government of ‘Rurban' Areas,” The American Political Science Review, Vol. 37, No. 2, April, 1943. -176- Reeder, L. 3., ”Industrial Decentralization as a Factor in Rural-Urban Fringe Development,” Land Economics, Vol. 31, No.3, August, 1955. Renne, Roland R., Land Economics, Harper and Brothers, New York, 1947. Robertson, Lynn, Changes in Pa ming_ in Lake and Porter Counties, Indiana, As a Result of Nearness to Industrial Cities, Purdue Agricultural Experiment Station Bulletin 365, Lafayette, 1932. Robertson, Lynn, The Economic Significance Lf the Non-Farming Rural Population in Northwestern Indiana, Purdue Agricultural Experiment Station Bulletin 388, Lafayette, 1934. Rodehaver, Myles, W., ”Fringe Settlement as a Two Directional Movement,” Rural Sociology, Vol. 12, No. 1, March, 1947. Rozeman, D., Part-Time Farming in Massachusetts, Massachusetts Agricultural Experiment Station Bulletin —266, Amherst, 1930. Salter, Leonard A., “Land Classification Along the Rural-Urban Fringe, Proceedings Lf the First National Conference Ln Land Classification, Missouri Agricultural Experiment Station, Bulletin 421, Columbia, 1940. Salter, Leonard A., Land Economics, The University of Minnesota Press, Minneapolis, 1948. Salter, Leonard A., and H. D. Darling, Part-Time Farming in Connecticut -- A Socio-Economic Study of the Lower Naugatuck Valley, Storrs Agric- ultural Experiment Station Bulletin 204, Storrs, 1935. Salter, Leonard A., and L. F. Diehl, ”Part-Time Farming Research,” Journal of FarmAEconomics, Vol. 22, No. 3, August, 1940. Thompson, Warren 8., Population Problems, McGraw-Hill Book Co., Inc., New York, 1942. United States Department of Agriculture, 1957 Agricultural Qutlook Charts, Agricultural Marketing Service and AgricUltural Research Service, Washington, D. C., November, 1956. United States Department of Agriculture, Basic Land Use Statistics, 1950, Supplement to "Major Uses of Land in the United States," Technical Bulletin 1082, United States Department of Agriculture, Bureau of Agricultural Economics, Washington, D. C., September, 1953. United States Department of Agriculture, Changes in Farm Production and Efficiency: 1955 Summary, Agricultural Research Service, Washington, D. C., ARS 43- 33, June, 1956. United States Department of Commerce, 1930 United States Census Lf Agr - culture: The Northern States, Bureau of the Census, United States Government Printing Office, Washington, D. C., Vol. II, part], 1932. -l77- United States Department of Commerce, 1930 United States Census 9: Agri- culture: Minor Civil Divisions, Michigan, Bureau of the Census, Washington, D. C, 1932. United States Department of Commerce, 1940 United States Census of Agri- culture: Minor Civil Divisions, Michigan, Bureau of the Census, Washington, D. C., 1942. United States Department of Commerce, 1940 United States Census of Agri: culture: Statistics for Counties, Bureau of the Census, United States Government Printing Office, Washington, D. C., Vol. I, part 1, 1942. United States Department of Commerce, 1950 United States Census of Agrio culture: General Report, Bureau of the Census, Washington, D. C., Vol. II, 1952. United States Department of Commerce, 1950 United States Census of Agri- culture: Michigan, Bureau of the Census, United States Government Printing Office, Washington, D. C., Vol. II, part 22,1952. United States Department of Commerce, 1950 United States Census of Agri— culture: Minor Civil Divisions, Michigan, Bureau of the Census, United States Government Printing Office, Washington, D. C., 1952. Unites State Department of Commerce, 1950 United States Census of ngula_tion: General Characteristics1,Michigan, Bureau of the Census, United States Government Printing Office, Washington, D. C., 1952. Usoem, John, “Does Decentralization Industry Mean Greater Security? The Case of Massachusetts,‘ Rural Sociology, Vol. 6, No. 1, March, 1941. Wehrwein, George 3., “The Rural-Urban Fringe," Economic Geography, Vol. 18, July, 1942. Wehrwein, George 5., ”Land Classification for Rural Zoning," Proceedings of the First National Conference on Land Classification, Missouri Agricultural Experiment Station Bulletin 421, Columbia, 1940. Wooten, H. H., Major Uses of Land in the United States, Bureau of Agri- cultural Economics, United States Department of Agriculture, Washing- ton, D. C., Technical Bulletin 1082, October, 1953. Zimmerman, Erich W., World Resources and Industries, Harper and Brothers, New York, 1951. APPENDIX -179- Appendix Table A Motor Vehicles and Specified Machines on Farms, United States, January 1, 1910-1955a : : : : Farms :Field Year : Tract- : Motor-x Auto- : Grain : Corn : udth :Pickup :forage : orsb : trucks:mobilesxcombinespickers:milking :balers : har- : : : :machines: :vesters (0007 (000) (000) (000) ’(000) (000) (000) (0007— 1910 1 0 50 1 -- 12 -- ~- 1920 246 139 2,146 4 10° 55 -- -- 1930 920 900 4,135 61 50 100 -- -- 1940 1,545 1,047 4,144 190 110 175 -- -- 1941 1,665 1,095 4,330 225 120 210 -- —- 1942 1,860 1,160 4,670 275 130 255 25c -- 1943 2,055 1,280 4,350 320 138 275 31 -- 1944 2,160 1,385 4,185 345 146 300 34 -- 1945 2,354 1,490 4,148 375 168 365 42 20° 1946 2,480 1,550 4,260 420 203 440 54 25 1947 2,617 1,700 4,350 465 236 525 65 30 1948 2,821 1,900 4,225 535 299 575 90 45 1949 3,123 2,065 4,290 620 372 610 135 60 1950 3,394 2,207 4,199 714 456 636 196 81 1951 3,678 2,310 4,220 810 522 655 240 102 1952 3,907 2,410 4,230 887 588 675 298 124 1953 4,100 2,520 4,240 930 630 690 345 148 1954 4,243 2,610 4,250 965 660 705 395 175 1955 4,345 2,701 4,258 980 688 712 448 202 aSource: Changes in Farm Production and Efficiency: 1955 Summary, United States Department of Agriculture, Agricultural Research Service, Washington, Table 16, pp. 38-39. D. C., ARS 43- 33, June, 1956, bEnumeration excludes steam and garden tractors. cInformation for earlier years not available. -180- 304.0 000.0 030.0 000.3 000.0 000.0 303.03 300.00 040.00 300 .0.030 0 000.43 040.03 000.03 003.0 300.0 403.03 030.00 044.00 000.00 3030 .0.000 000 030.43 000.03 433.43 000.0 000.4 000.33 030.03 330.00 000.00 3030 .0.030 mm 000.03 000.03 000.43 000.4 000.0 000.43 030.00 000.00 000.40 3030 .0.030 000 000.03 000.03 004.03 000.0 000.4 000.03 000.03 004.00 000.00 3030 .0.000 0 040.03 043.33 000.0 000.03 000.0 000.03 300.00 003.00 030.00 3030 0.000 020 000.03 004.03 000.03 000.0 300.0 000.03 000.00 000.00 044.00 3030 .0.030 02 Hmwu. Ucouwm 000.303 000.003 030.00 404.000 000.000 400.000 400.000 000.004 003.000 30033 30000 000.03 000.03 004.0 400.00 003.30 004.04 000.04 040.00 303.00 3030 .0.020 2 000.03 000.03 333.03 000.43 040.00 000.00 000.00 000.44 000.00 3030 .0.030 32 000.0 400.03 300.0 030.03 003.00 030.00 000.00 303.34 000.00 3030 .0.030 x 030.03 000.03 030.03 304.00 000.00 000.00 303.00 003.00 030.003 3000 .0.000 :0 300.0 000.03 004.0 033.00 400.00 000.00 000.04 030.30 000.40 3030 .0.030 0 000.43 000.03 000.43 000.00 400.00 000.00 040.00 300.00 400.003 3030 .0.030 00 003.03 044.43 000.03 400.43 034.03 000.00 040.00 000.04 004.00 3030 .0.030 0 303.03 000.00 004.03 030.04 000.40 400.30 000.30 000.00 000.003 3033 .0.030 02 - 0030 00030 000.0 040.0 040.4 300.00 000.00 030.30 400.40 000.04 000.00 3030 .0.000 000000 0003 . 0403 . 0003 . 0003 0 0403 . 0003 . 0003 . .0403. . 0003 0 0030 000 c00003saoq 500m 0 ocowwmasmoa anmmccoc amusm 0 c00003zaoa 3000b 0 becaumooa . 0 . aflzmcsoh 00000< >000 pwaamz H3< .0000 6:0 coflumooq awcmcgok >n c00003saoa amuoh 0 03000 03000004 .0403 000 0003 000 0030030000 0000 :00: 30030 0:0 00000000>o 0030 :03:3 .00000 00x0ccm 0:0 mo 0:030033000 0:0 >030000 00: 0000 0:0:00 0:0 .0530 00 003000 03:0 mC30=n 0:0300x0ccm 00 00:55: 0m003 m 0003 000:0 .00303000 :3 .0403 new omo3 :3 0000333> 0:0 003030 000:0 00 0030033000 30000 0:0 >: 00000000>o 0000000:0 03 :030035500 5000150: 300nm .030000 0003 0:0 C3 0530 00030 0:0 000 000033 3003mm3 «0 30000 c03003zaoq a :03: .ovo3 00:30 00000oa0ooc3 0>0: 00:0 003030 0:0 0000333> 0cm c300 0000000000030: mm 000 000:0 0030033000 03:0 030 .>030 3000:00 0:0 00 0000000 :03; c0303moa 3000300003 :000 :3 003:0c300 00 00:53: 0:0 00003023 0000:0c00ma :3 0000522: .0003 .00 0000 .33 .30> 3.0 :3 .co0mcmmmmslhmswc0o 0:0 06 50003m .0000550mlmo 0:05000009 0000m 0003:: .cmm3:03: .CO3003smoa 0:0 00 003003000000~:U 3:03003amma mo 050:00 00000m 0003c: 0003 3000:0m0 .0 000.003 000.030 003.003 004.00 000.033 000.000 400.000 004.034 000.000 30000 30000 8 .3 000.03 300.03 004.03 000.0 000.03 000.40 000.00 004.00 040.04 3030 0.030 022 430.0 000.03 000.0 003.4 000.0 030.0 000.00 400.00 000.00 3030 0.020 2 000.43 000.03 000.43 000.4 344.4 000.03 040.30 000.00 000.30 3030 0.000 :22 400.33 004.03 000.33 000.3 004.0 003.0 040.03 000.03 000.00 3030 .0.030 :2 400.03 000.03 030.03 400.0 000.0 000.03 000.30 000.00 300.00 3430 .0.020 :2; 000.0 003.0 034.0 000.03 000.03 030.00 003.00 000.40 003.00 300 .0.030 x 000.43 000.03 000.43 300.0 300.33 003.40 000.40 000.00 000.04 3033 .0.030 :0; 000.03 030.03 300.03 330.0 000.0 300.03 300.00 000.40 000.00 3430 .0.030 :0 040.43 000.03 000.43 300.0 000.0 303.03 400.00 000.00 000.00 3030 .0.020 :00 .n.0coo 0030 0:000m omo3 3 0403 3 0003 3 omo3 3 ovo3 3 0003 3 0mo3 3 ovo3 3 0003 3 :0030 new c03003zmwm1500m 3 0:03003550Q150mmucoc 3003m 3 003003smoa 30000 3 c030moo3 3 3 3 53:05:00 003:30500 m 03:00 x3pc000< ~182- Appendix Table C Farms and Farm Acreages by Township Location and Tier, All Mapped City Areasa Township 3 3 location 1 Number of farms : Total acres in farms I and tier 3 1950 : 1940 x 1930 x 1950 a 1940 s 1930 ' Center twp's (10) 1,004 1,383 1,621 104,783 107,735 121,234 First tier NE twp's.(18) 3,070 4,281 3,423 256,327 278,904 269,763 E twp's,(13) 2,301 2,940 2,442 199,523 215,849 198,812 SE twp's.(18) 3,119 3,649 3,227 267,320 284,172 269,888 8 twp's. (15) 1,827 2,611 2,129 172,304 199,167 185.635 sw twp's. (20) 2,859 3,748 3,321 260,775 293,661 287,663 w twp's. (12) 1,838 2,296 2,053 165,850 193,866 188,514 Nw twp's. (17) 2,636 3,575 2,698 260,415 288,589 260,824 N twp's. (12) 1,618 2,613 1,806 172,922 190,361 181,376 Total (125) 19,268 25,713 21,099 1,755,436 1,944,569 1,842,475 Second tier NE twp's. (17) 2,535 3,064 2,762 280,749 312,595 299,359 ENE twp's. (13) 2,062 2,422 2,018 205,860 219,346 194,768 T twp'S. (13) 2,359 2,702 2,484 203,928 212,257 225,609 ESE twp's (15) 2,878 3,215 2,859 259,950 269,540 258,691 SE twp's. (15) 2,836 3,110 3,124 285,941 285,996 294,136 838 twp's. (15) 2,667 3,803 2,920 272,500 288,679 266,734 5 twp's. (9) 1,530 1,721 1,648 168,667 175,705 165,971 ssw twp's. (16) 2,614 3,568 2,789 252,140 295,411 252,357 sw twp's. (14) 2,750 3,436 3,009 245.703 264,346 254,116 wsw twp's. (15) 3,018 3,830 3,290 278,818 282,862 291,873 w twp's. (9) 1,364 1,691 1,593 134,001 153,247 150,650 WNW twp'S. (14) 2,368 2,968 2,330 247,152 265,259 247,000 Nw twp's. (15) 2,519 2,904 2,744 259,721 280,639 281,405 NNw twp's. (18) 3,065 3,424 2,986 307,125 311,046 297,438 N twp's (12) 1,969 2,206 2,316 205,827 219,005 231,939 NNE twp's. (17) 2,737 3,377 2,647 271,167 306,788 271,637 Total (227) 39,271 47,441 41,517 3,879,249 4,142,721 3,983,683 8Source: 1930, 1940, and 1950 United States Census of Agriculture: Minor Civil Envisions, Michigan, United States Department of Commerce, Bureau of the Census, Washington, D. C. bNumbers in parentheses indicate the number of townships in each locational position with reSpect to the central city. Appendix Table C continued -183— Township 3 3 location 3 Acres of cropland harvested 3 Acres of cropland idle and tier 3 1950 x 1940 s 1930 3 1950 x 1940 s 1930 Center twp's. (10) 52,327 52,633 60,455 48,716 6,427 13,610 First tier NE twp's.(18) 133,744 136,346 139,450 24,411 23,022 24,602 E twp'S. (13) 110,942 112,878 105,313 13,431 15,369 17,815 SE twp's. (18) 148,363 152,637 144,492 20,682 15,286 20,968 5 twp'S. (15) 84,330 94,534 88,369 14,882 15,606 19,494 5w twp's. (20) 138,528 141,462 143,794 17,389 25,132 25,692 w twp's. (12) 85,773 94,240 93,381 15,092 13,169 14,868 Nw twp'S. (17) 132,384 139,739 127,080 22,834 24,402 26,422 N twp's. (12) 89,037 124,683 89,455 14,407 12,874 17,722 Total (125) 923,101 996,519 931,334 142,128 144,860 167,583 Second tier NE twp's. (17) 141,749 140,584 139,518 19,479 20,995 23,297 ENE twp‘S. (13) 103,300 102,968 96,998 14,731 16,146 17,358 E twp'S. (13) 116,171 112,369 115,481 14,110 15,229 20,508 ESE twp's. (15) 143,027 141,305 138,461 20,200 14,237 18,350 SE twp's. (15) 160,705 140,085 152,069 20,033 15,821 23,319 SSE twp's. (15) 156,379 152,772 140,840 17,196 13,647 21,933 5 twp's. (9) 88,154 93,830 82,307 12,787 9,248 15,766 ssw twp's. (16) 139,436 147,827 127,425 18,165 23,308 21,158 sw twp's. (14) 131,790 134,134 131,581 19,675 20,068 21,150 wsw twp's. (15) 143,915 138,635 147,000 21,762 22,942 23,322 N twp's. (9) 68,115 86,735 73,085 11,334 8,961 13,844 WNW twp's. (14) 123,733 130,876 119,510 19,495 17,471 19,439 Nw twp's. (15) 128,869 132,446 135,826 20,854 17,762 22,271 NNw twp's. (18) 159,313 148,634 147,065 20,798 23,275 27,317 N twp's. (12) 102,929 102,497 111,051 13,741 16,903 20,722 NNE twp's. (17) 132,440 140,025 132,508 20,922 23,207 24,468 Total (227) 2,040,025 2,035,722 1,990,725 285,282 279,220 334,222 -184— APPENDIX TABLE D-l Per Cent Rural Non-Farm Population (X) and Average Acres Per Farm (Y), by County, 1950a '._- fl County X Y X2 Y2 XY Sanilac 15.3 124.6 234.09 15,525.16 1,906.38 Huron 19.9 129.6 396.01 16,796.16 2,579.04 Montcalm 27.3 116.4 745.29 13,548.96 3,177.72 Van Buren 27.6 82.4 761.76 6,789.76 2,274.24 Hillsdale 31.5 103.5 992.25 10,712.25 3,260.25 Shiawassee 31.8 108.5 1,011.24 11,772.25 3,450.30 Isabella 32.7 127.9 1,069.29 16,358.41 4,182.33 Tuscola 32.8 110.2 1,075.85 12,144.04 3,614.56 Gratiot 33.0 114.8 1,089.00 13,179.04 3,788.40 Barry 35.2 115.3 1,239.04 13,294.09 4,058.56 Eaton 36.5 107.5 1,332.25 11,556.25 3,823.75 St. Joseph 36.8 132.2 1,354.24 17,476.84 4,864.96 Allegan 37.7 84.9 1,421.29 7,208.01 3,200.73 Branch 38.2 119.9 1,459.24 14,376.01 4,580.18 Clinton 40.8 121.0 1,664.64 14,641.00 4,936.80 Lapeer 40.8 116.6 1,664.64 13,595.56 4,757.28 Ionia 40.8 125.5 1,664.64 15,750.25 5,120.40 Lenawee 45.5 112.7 2,070.25 12,701.29 5,127.85 Cass 45.6 111.3 2,079.36 12,387.69 5,075.28 Livingston 50.5 135.9 2,550.25 18,468.81 6,862.95 Ottawa 52.0 72.2 2,704.00 5,212.84 3,754.40 Berrien 53.4 60.1 2,851.56 3,612.01 3,209.34 St. Clair 54.0 94.5 2,916.00 8,930.25 5,103.00 Monroe 54.4 81.0 2,959.36 6,561.00 4,406.40 Bay 54.9 81.3 3,014.01 6,609.69 4,463.37 Calhoun 55.5 120.4 3,080.25 14,496.16 6,682.20 Midland 56.1 101.3 3,147.21 10,261.69 5,682.93 Jackson 64.1 123.5 4,108.81 15,252.25 7,916.35 Saginaw 64.5 94.4 4,160.25 8,911.36 6,088.80 Ingham 72.7 115.0 5,285.29 13,225.00 8,360.50 Washtenaw 75.9 124.2 5,760.81 15,425.64 9,426.78 Kent 77.8 90.2 6,052.84 8,136.04 7,017.56 Kalamazoo 80.2 105.9 6,432.04 11,214.81 8,493.18 Genessee 81.9 79.4 6,707.61 6,304.36 6,502.86 Macomb 83.8 63.2 7,022.44 3,994.24 5,296.16 Muskegon 84.8 81.6 7,191.04 6,658.56 6,191.68 Oakland 90.6 91.9 8,208.36 8,445.61 8,326.14 Wayne 90.7 48.0 8,226.49 2,304.00 4,352.60 Totals 1,947.6 3,928.8 115,702.98 423,837.34 192,745.21 aSource: See Page 1966 A ‘ ”3“?!” LA . mi an o x 3'3 APPENDIX TABLE D-2 -185- Per Cent Rural Non-Farm Population (X) and Per Cent of Total Farm in Cropland (Y), by County, 1950a . County X Y X2 Y XY Sanilac 15.3 57.5 234.09 3,306.25 879.75 Huron 19.9 64.0 396.01 4,096.00 1,273.60 Montcalm 27.3 43.5 745.29 1,892.25 1,187.55 Van Buren 27.6 46.0 761.76 2,116.00 1,269.60 Hillsdale 31.5 51.5 992.25 2,652.25 1,622.25 Shiawassee 31.8 57.1 1,011.24 3,260.41 1,815.78 Isabella 32.7 48.2 1,069.29 2,323.24 1,576.14 Tuscola 32.8 59.0 1,075.84 3,481.00 1,935.20 Gratiot 33.0 60.8 1,089.00 3,696.64 2,006.40 Barry 35.2 44.3 1,239.04 1,962.49 1,559.36 Eaton 36.5 53.0 1,332.25 2,809.00 1,934.50 St. Joseph 36.8 48.9 1,354.24 2,391.21 1,799.52 Allegan 37.7 50.9 1,421.29 2,590.81 1,918.93 Branch 38.2 52.6 1,459.24 2,766.76 2,009.32 Clinton 40.8 56.0 1,664.64 3,136.00 2,284.80 Lapeer 40.8 47.9 1,664.64 2,294.41 1,954.32 Ionia 40.8 51.6 1,664.64 2,662.56 2,105.28 Lenawee 45.5 64.6 2,070.96 4,044.96 3,893.80 Cass 45.6 46.5 2,079.36 2,162.25 2,120.40 Livingston 50.5 43.8 2,550.25 1,918.44 2,211.90 Ottawa 52.0 52.5 2,704.00 2,756.25 2,730.00 Berrien 53.4 57.4 2,851.56 3,294.76 3,065.16 St. Clair 54.0 51.0 2,916.00 2,601.00 2,754.00 Ionroe 54.4 69.1 2,959.36 4,774.81 3,759.04 Bay 54.9 59.3 3,014.01 3,516.49 3,255.57 Calhoun 55.5 47.4 3,080.25 2,246.76 2,630.70 Midland 56.1 41.7 3,147.21 1,738.89 2,339.37 Jackson 64.1 44.0 4,108.81 1,936.00 2,820.40 Saginaw 64.5 57.9 4,160.25 3,352.41 3,734.55 Ingham 72.7 51.4 5,285.29 2,641.96 3,736.78 lashtenaw 75.9 51.2 5,760.81 2,621.44 3,886.08 Kent 77.8 45.3 6,052.84 2,052.09 3,524.34 Kalamazoo 80.2 49.2 6,432.04 2,420.64 3,945.84 Genessee 81.9 52.4 6,707.61 2,745.76 4,291.56 Macomb 83.8 56.8 7,022.44 3,225.24 4,759.84 Muskegon 84.8 38.2 7,191.04 1,459.24 3,239.36 Oakland 90.6 40.8 8,208.36 1,664.64 3,696.48 Wayne 90.7 54.6 8,226.49 2,981.16 4,952.22 Totals 1,947.6 1,966.9 115,702.98 103,593.47 99,479.69 aSource: See page 196. -186- APPENDIX TABLE D-3 Per Cent Rural Non-Faun Population (X) and Per Cent of Cropland in Grain Crops (Y), by County, 1950a County x Y x2 72 xv Sanilac 15.3 44.1 234.09 1,944.81 674.73 Huron 19.9 42.6 396.01 1,814.76 847.74 Montcalm 27.3 41.9 745.29 1,755.61 1,143.87 Van Buren 27 6 37.5 761.76 1,406.25 1,035.00 Hillsdale 31 5 63.7 992.25 4,057.69 2,006.55 Shiawassee 31 8 57.2 1,011.24 3,271.84 1,818.96 Isabella 32 7 51.5 1,069.29 2,652.25 1,684.05 Tuscola 32.8 47.4 1,075.84 2,246.86 1,554.72 Gratiot 33.0 58.5 1,089.00 3,422.25 1,930.50 Barry 35 2 53.9 1,239.04 2,905.21 1,897.28 Eaton 36 5 62.1 1,332.25 3,856.41 2,266.65 St. Joseph 36 8 58.0 1,354.24 3,364.00 2,134.40 Allegan 37 7 52.2 1,421.29 2,724.84 1,967.94 Branch 38 2 66.7 1,459.29 4,448.89 2,547.94 Clinton 40 8 62.2 1,664.64 3,868.84 2,537.76 Lapeer 40 8 49.8 1,664.64 2,480.04 2,031.84 Ionia 40.8 63.0 1,664.64 3,969.00 2,570.40 Lenawee 45 5 69.7 2,070.25 4,858.09 3,171.35 Cass 45 6 57.2 2,079.36 3,271.84 2,608.32 Livingston 50.5 52.4 2,550.25 2,745.76 2,646.20 Ottawa 52 0 58.2 2,704.00 3,387.24 3,026.40 Berrien 53 4 35.1 2,851.56 1,232.01 1,874.34 St. Clair 54 O 47.9 2,916.00 2,294.41 2,586.60 Monroe 54 4 62.1 2,959.36 3,856.41 3,378.24 Bay 54 9 40.0 3,014.01 1,600.00 2,196.00 Calhoun 55 5 60.6 3,080.25 3,672.36 3,363.30 Midland 56 1 44.4 3,147.21 1,971.36 2,490.84 Jackson 64 1 53.4 4,108.81 2,851.56 3,522.94 Saginaw 64 5 50.4 4,160.25 2,540.16 3,250.80 Ingham 72 7 58.5 5,285.29 3,422.25 4,252.95 Washtenaw 75.9 60.9 5,760 81 3,708.81 4,622.31 Kent 77.8 45.9 6,052 84 2,106.81 3,571.02 Kalamazoo 80.2 56.2 6,423 04 3,158.44 4,507.24 Genessee 81.9 52.8 6,707 61 2,787.84 7,324.32 Macomb 83.8 52.2 7,022 44 2,724.84 4,374.36 Muskegon 84.8 42,0 7,191 04 1,764.00 3,561.60 Oakland 90.6 44.8 8,208 36 2,007.04 4,058.88 Wayne 90.7 50.5 8,226 49 2,550.25 4,580.35 Totals 1,947.6 2,007.5 115,702.98 108,700.93 102,518.69 aSource: See page 196. Per Cent Rural Non-Faun Population (X) and Per Cent of Cropland in Hay and Legumes (Y), by County, 1950a —187- APPENDIX TABLE D-4 County x Y x2 72 xv Sanilac 15.3 41.3 234.09 1,705.69 631.89 Huron 19.9 47.0 396.01 2,209.00 935.30 Montcalm 27.3 32.7 745.29 1,069.69 892.71 Van Buren 27.6 16.7 761.76 278.89 460.92 Hillsdale 31.5 23.7 992.25 561.69 746.55 Shiawassee 31.8 29.1 1,011.24 846.81 925.38 Isabella 32.7 33.2 1,069.29 1,102.24 1,085.64 Tuscola 32.8 38.0 1,075.84 1,444.00 1,246.40 Gratiot 33.0 30.6 1,089.00 936.36 1,009.80 Barry 35.2 24.0 1,239.04 576.00 844.80 Eaton 36.5 22.6 1,332.25 510.76 824.90 St. Joseph 36.8 19.6 1,354.24 384.16 721.28 Allegan 37.7 20.2 1,421.29 408.04 761.54 Branch '38.2 23.0 1,459.24 529.00 878.60 Clinton 40.8 22.6 1,664.64 510.76 922.08 Lapeer 40.8 33.5 1,664.64 1,122.25 1,366.80 Ionia 40.8 23.3 1,664.64 542.89 950.64 Lenawee 45.5 20.0 2,070.25 400.00 910.00 Cass 45.6 17.6 2,079.36 309.76 802.56 Livingston 50.5 26.0 2,550.25 676.00 1,313.00 Ottawa 52.0 22.5 2,704.00 506.25 1,170.00 Berrien 53.4 11.7 2,851.56 136.89 624.78 St. Clair 54.0 34.1 2,916.00 1,162.81 1,841.40 Monroe 54.4 24.4 2,959.36 595.36 1,327.36 Bay 54.9 34.7 3,014.01 1,204.09 1,905.03 Calhoun 55.5 20.9 3,080.25 436.81 1,159.95 Midland 56.1 37.0 3,147.21 1,369.00 2,075.70 Jackson 64.1 24.7 4,108.81 610.09 1,583.27 Saginaw 64.5 35.1 4,160.25 1,232.01 2,263.95 Ingham 72.7 22.1 5,285.29 488.41 1,607.67 Washtenaw 75.9 25.3 5,760.81 640.09 1,920.27 Kent 77.8 26.5 6,052.84 702.25 2,061.70 Kalamazoo 80.2 19.9 6,432.04 396.01 1,595.98 Genessee 81.9 27.9 6,707.61 778.41 2,285.01 Macomb 83.8 24.4 7,022.44 595.36 2,044.72 Muskegon 84.8 27.8 7,191.04 772.84 2,357.44 Oakland 90.6 26.0 8,208.36 676.00 2,355.60 Wayne 90.7 21.8 8,226.49 475.24 1,977.26 Totals 1,947.6 1,011.5 115,702.98 28,901.91 50,387.88 aSource: See page 196. s 7:.” :3 — 77’ I -188- APPENDIX TABLE D-5 Per Cent Rural Non-Farm P0pu1ation (X) and Per Cent of Cropland in Other Crops (Y), by County, 1950a 2 County x Y x2 v xv Sanilac 15.3 6.7 234.09 44.89 102.51 Huron 19.9 6.0 396.01 36.00 119.40 Montcalm 27.3 7.4 745.29 54.76 202.02 Van Buren 27.6 20.2 761.76 408.04 557.52 Hillsdale 31.5 1.8 992.25 3.24 56.70 Shiawassee 31.8 3.0 1,011.24 9.00 95.40 Isabella 32.7 4.6 1,069.29 21.16 150.42 Tuscola 32.8 7.4 1,075.84 54.76 242.72 Gratiot 33.0 4.3 1,089.00 18.49 141.90 Barry 35.2 3.4 1,239.00 11.56 119.68 Eaton 36.5 4.5 1,332.25 20.25 164.25 St. Joseph 36.8 4.1 1,354.24 16.81 150.88 Allegan 37.7 9.3 1,421.29 86.49 350.61 Branch 38.2 2.8 1,459.24 7.84 106.96 Clinton 40.8 5.6 1,664.64 31.36 228.48 Lapeer 40.8 4.6 1,664.64 21.16 187.68 Ionia 40.8 2.5 1,664.64 6.25 102.00 Lenawee 45.5 4.5 2,070.25 20.25 204.75 Cass 45.6 5.3 2,079.36 28.09 241.68 Livingston 50.5 4.8 2,550.25 23.04 242.40 Ottawa 52.0 5.5 2,704.00 30.25 286.00 Berrien 53.4 37.3 2,851.56 1,391.29 1,991.82 St. Clair 54.0 4.9 2,916.00 24.01 246.60 Monroe 54.4 6.6 2,959.36 43.56 359.04 Bay 54.9 15.9 3,014.01 252.81 872.91 Calhoun 55.5 5.0 3,080.25 25.00 277.50 Midland 56.1 6.2 3,147.21 38.44 347.82 Jackson 64.1 5.7 4,108.81 32.49 365.37 Saginaw 64.5 5.5 4,160.25 30.25 254.75 Ingham 72.7 5.8 5,285.29 33.64 421.66 lashtenaw 75.9 4.1 5,760.81 16.81 311.19 Kent 77.3 9.4 6,052.84 88.36 731.32 Kalamazoo 80.2 5.6 6,432.04 31.36 449.12 Genessee 81.9 4.7 6,707.61 22.09 384.93 Macomb 83.8 11.8 7,022.44 139.24 988.84 Muskegon 84.8 9.1 7,191.04 82.81 771.68 Oakland 90.6 8.5 8,208.36 72.25 770.10 Mayne 90.7 13.0 8,226.49 169.00 1,179.10 —'1'ota1s 1,94‘T7. "'_T77—TT5—02'9'8—.4 ,7 . "TT?, ‘4 .10 14,89527‘1“ aSource: See page 196. fie --O . . -—.7.I . ¢.‘. N -189- APPENDIX TABLE D-6 Per Cent Rural Non-Farm Population (X) and Per Cent of Cropland Idle (Y), by County, 1950a County x Y x2 v2 xv Sanilac 15.3 8.0 234.09 64.00 122.40 Huron 19.9 4.4 396.01 19.36 87.56 Montcalm 27.3 18.0 745.29 324.00 491.40 Van Buren 27.6 25.5 761.76 650.25 703.80 Hillsdaie 31.5 10.7 992.25 114.49 337.05 Shiawassee 31.8 10.7 1,011.24 114.49 340.26 Isabella 32.7 10.6 1,069.29 112.36 346.62 Tuscola 32.8 7.1 1,075.84 50.41 232.88 Gratiot 33.0 6.3 1,089.00 39.69 207.90 Barry 35.2 17.0 1,239.04 289.00 598.40 Eaton 36.5 10.7 1,333.25 114.49 390.55 St. Joseph 36.8 18.3 1,354.24 334.89 673.44 Allegan 37.7 17.7 1,421.29 313.29 667.29 Branch 38.2 7.6 1,459.24 57.76 290.32 Clinton 40.8 9.5 1,664.64 90.25 387.60 Lapeer 40.8 12.0 1,664.64 144.00 ' 489.60 Ionia 40.8 11.2 1,664.64 125.44 456.96 Lenawee 45.5 5.7 2,070.25 32.49 259.35 Cass 45.6 20.0 2,079.36 400.00 912.00 Livingston 50.5 16.8 2,550.25 282.24 848.40 Ottawa 52.0 13.9 2,704.00 193.21 722.80 Berrien 53.4 15.9 2,851.56 252.81 849.06 St. Clair 54.0 13.2 2,916.00 174.24 712.80 Monroe 54.4 7.0 2,959.36 49.00 380.80 Bay 54.9 9.6 3,014.01 92.16 527.04 Calhoun 55.5 13.5 3,080.25 182.25 749.25 Midland 56.1 12.3 3,147.21 151.29 690.03 Jackson 64.1 17.1 4,018.81 292.41 1,096.11 Saginaw 64.5 9.0 4,160.25 81.00 580.50 Ingham 72.7 13.6 5,285.29 184.96 988.72 lashtenaw 75.9 9.7 5,760.81 94.09 736.23 Kent 7758 18.3 6,052.84 334.89 1,423.74 Kalamazoo 80.2 18.5 6,432.04 342.25 1,483.70 Genesee 81.9 14.6 6,707.61 213.16 1,195.74 Macomb 83.8 11.6 7,022.44 134.56 972.08 Muskegon 84.8 21.0 7,191.04 441.00 1,780.08 Oakland 90.6 20.7 8,208.36 428.49 1,875.42 layne 90.7 14.7 8,226.49 216.09 1,333.29 "‘7TSta1s 1.9I7TE"""502.0 1151102.98 ' 772536776 26,941.17 aSource: See page 196. Per Cent Rural Non-Farm P0pu1ation (X) and Per Cent -190- APPENDIX TABLE D-7 of Farmland in Pasture (Y), by County, 1950a County x Y x2 Y2 XY Sanilac 15.3 28.2 234.09 795.24 431.46 Huron 19.9 23.1 396.01 533.61 459.69 Montcalm 27.3 29.0 745.29 841.00 791.70 Van Buren 27.6 20.4 761.76 416.16 563.04 Hillsdale 31.5 28.3 992.25 800.89 891.45 Shiawassee 31.8 21.8 1,011.24 475.24 693.24 Isabella 32.7 33.0 1,069.29 1,089.00 1,079.10 Tuscola 32.8 22.5 1,075.84 506.25 738.00 Gratiot 33.0 24.9 1,089.00 620.01 821.70 Barry 35.2 29.1 1,239.04 846.81 1,024.32 Eaton 36.5 27.4 1,332.25 750.76 1,000.10 St. Joseph 36.8 22.3 1,354.24 497.29 820.64 Allegan 37.7 17.4 1,421.29 302.76 655.98 Branch 38.2 29.6 1,459.24 876.16 970.88 Clinton 40.8 24.5 1,664.64 600.25 999.60 Lapeer 40.8 29.8 1,664.64 888.04 1,215.84 Ionia 40.8 29.4 1,664.64 864.36 1,199.52 Lenawee 45.5 20.0 2,070.25 400.00 910.00 Cass 45.6 22.4 2,079.36 501.76 1,021.44 Livingston 50.5 27.5 2,550.25 756.25 1,388.75 Ottawa 52.0 26.2 2,704.00 686.44 1,362.40 Berrien 53.4 16.1 2,851.56 259.21 859.74 St. Clair 54.0 29.2 2,916.00 852.64 1,576.80 Monroe 54.4 11.6 2,959.36 134.56 631.04 Bay 54.9 24.4 3,014.01 595.36 1,339.56 Calhoun 55.5 29.4 3,080.25 864.36 1,631.70 Midland 56.1 35.3 3,147.21 1,246.09 1,980.33 Jackson 64.1 27.9 4,108.81 778.41 1,788.39 Saginaw 64.5 22.6 4,160.25 519.76 1,457.70 Ingahm 72.7 27.0 5,285.29 729.00 1,962.90 Washtenaw 75.9 28.1 5,760.81 789.61 2,132.79 Kent 77.8 21.7 6,052.84 470.89 1,688.26 Kalamazoo 80.2 24.0 6,432.04 576.00 1,924.80 Genesee 81.9 24.2 6,707.61 585.64 1,981.98 Macomb 83.8 23.1 7,022.44 533.61 1,935.78 Muskegon 84.8 28.4 7,191.04 806.56 2,408.32 Oakland 90.6 26.3 8,208.36 691.69 2,382.78 Wayne 90.7 19.0 8,226.49 361.00 1,723.30 Totals 1,947.6 955.10 115,702.98 24,833.67 48,445.02 aSource: See page 196. W- .‘ _.4 .5- J Per Cent Rural Non-Farm Population (X) and Animal Units -191- APPENDIX TABLE D-8 Per Acre of Pasture by County, 1950a County )1 Y x2 Y2 xv Sanilac 15.3 .30 234.09 .090 4.59 Huron 19.9 .31 396.01 .096 6.17 Montcalm 27.3 .23 745.29 .053 6.28 Van Buren 27.6 .24 761 .76 .058 6.62 Hillsdale 31.5 .31 992.25 .086 9.77 Shiawassee 31.8 .35 1,011.24 .123 11.13 Isabella 32.7 .23 1,069.29 .053 7.52 Tuscola 32.8 .27 1,075.84 .073 8.86 Gratiot 33.0 .30 1,089.00 .090 9.90 Barry 35.2 .24 1,239.04 .058 8.45 Eaton 36.5 .28 1,332.25 .078 10.22 St. Joseph 36.8 .25 1,354.24 .063 9.20 Allegan 37.7 .51 1,421.29 .260 19.23 Branch 38.2 .27 1,459.24 .073 10.31 Clinton 40.8 .30 1,664.64 .090 12.24 Lapeer 40.8 .28 1,664.64 .078 11.42 Ionia 40.8 .27 1,664.64 .073 11.02 Lenawee 45.5 .33 2,070.25 .109 15.02 Cass 45.6 .24 2,079.36 .058 10.94 Livingston 50.5 .24 2,550.25 .058 12.12 Ottawa 52.0 .41 2,704.00 .168 21.32 Berrien 53.4 .30 2,851.56 .090 16.02 St. Clair 54.0 .29 2,916.00 .084 15.66 Monroe 54.4 .48 2,959.36 .230 26.11 Bay 54.9 .26 3,014.01 .068 14.27 Calhoun 55.5 .23 3,080.25 .053 12.77 Midland 56.1 .15 3,147.21 .023 8.42 Jackson 64.1 .23 4,108.81 .053 14.74 Saginaw 64.5 .28 4,160.25 .078 18.06 Ingham 72.7 .27 5,285.29 .073 19.63 Washtenaw 75.9 .29 5,760.81 .084 22.01 Kent 77.8 .36 6,052.84 .130 28.01 Kalamazoo 80.2 .22 6,432.04 .048 17.64 Genessee 81.9 .30 6,707.61 .090 24.57 Macomb 83.8 .44 7,022.44 .194 36.87 Muskegon 84.8 .25 7,191.04 .063 21.20 Oakland 90.6 .24 8,208.36 .058 21.74 Wayne 90.7 .37 8,226.49 .137 33.56 ""Tota1s 1,947T6 11.12 115,702.98 3.454 573761""’ aSource: See page 196. APPENDIX TABLE D-9 -l92- Per Cent Rural Non-Farm Population (X) and Per Cent of all Farms Less Than Fifty Acres, by County, 1950a 11 County x Y x2 Y2 XY Sanilac 15.3 15.8 234.09 249.64 241.74 Huron 19.9 13.5 396.01 182.25 268.65 Montcalm 27.3 19.2 745.29 368.64 524.16 Van Buren 27.6 42.7 761.76 1,823.29 1,178.52 Hillsdale 31.5 26.3 992.25 691.69 828.45 Shiawassee 31.8 25.0 1,011.24 625.00 795.00 Isabella 32.7 20.3 1,069.29 412.09 663.81 Tuscola 32.8 21.9 1,075.85 479.61 718.32 Gratiot 33.0 22.9 1,089.00 524.41 755,70 Barry 25.2 23.2 1,239.04 538.24 816.64 Eaton 36.5 28.2 1,332.25 795.24 1,029.30 St. Joseph 36.8 23.2 1,354.24 538.24 853.76 Allegan 37.7 34.0 1,421.29 1,156.00 1,281.80 Branch 38.2 24.3 1,459.24 590.49 928.26 Clinton 40.8 22.5 1,664.64 506.25 918.00 Lapeer 40.8 21.3 1,664.64 453.69 869.04 Ionia 40.8 21.7 1,664.64 470.89 885.36 Lenawee 45.5 24.4 2,070.25 595.36 1,110.20 Cass 45.6 28.7 2,079.36 823.69 1,308.72 Livingston 50.5 20.2 2,550.25 408.04 1,020.10 Ottawa 52.0 39.5 2,704.00 1,560.25 2,054.00 Berrien 53.4 62.6 2,851.56 3,916.76 3,342.84 St. Clair 54.0 29.9 2,916.00 894.01 1,614.60 Monroe 54.4 41.1 2,959.36 1,689.21 2,235.84 Bay 54.9 33.7 3,014.01 1,135.69 1,850.13 Calhoun 55.5 26.5 3,080.25 702.25 1,470.75 Midland 56.1 28.7 3,147.21 823.69 1,610.07 Jackson 64.1 26.2 4,108.81 686.44 1,679.42 Saginaw 64.5 30.6 4,160.25 936.36 1,973.70 Ingham 72.7 28.8 5,285.29 829.44 2,093.76 Mashtenaw 75.9 26.4 5,760.81 696.96 2,003.76 Kent 77.8 36.6 6,052.84 1,339.56 2,847.48 Kalamazoo 80.2 37.3 6,423.04 1,391.29 2,991.46 Geneaee 81.9 46.5 6,707.61 2,162.25 3,808.35 Macomb 83.8 53.0 7,022.44 2,809.00 4,441.40 Muskegon 84.8 45.7 7,191.04 2,088.49 3,875.36 Oakland 90.6 48.1 8,208.36 2,313.61 4,357.86 Wayne 90.7 80.9 8,226.49 5,026.81 6,430.63 “'Tota1s 1,947.6 1 191.4 5,702.98 43,236.82 67,676.94 aSource: See page 196. APPENDIX TABLE D-lO -193- Per Cent Rural Non-Farm Population (X) and Per Cent of all Farms With Less Than $1,000 Value of Products Sold (Y),by County, 1950a W County x Y x2 Y2 xv Sanilac 15.3 18.9 234.09 357.21 289.17 Huron 19.9 13.3 396.01 176.89 264.67 Montcalm 27.3 32.8 745.29 1,075.84 895.44 Van Buren 27.6 42.6 761.76 1,814.76 1,175.76 Hillsdale 31.5 32.3 992.25 1,043.29 1,017.45 Shiawassee 31.8 27.1 1,011.24 734.41 861.78 Isabella 32.7 25.7 1,069.29 660.49 840.39 Tuscola 32,8 27.3 1,075.84 745.29 895.44 Gratiot 33.0 20.8 1,089.00 432.64 686.40 Barry 35.2 36.3 1,239.04 1,317.69 1,277.76 Eaton 36.5 30.8 1,332.25 948.64 1,124.20 St. Joseph 36.8 30.7 1,354.24 942.49 1,129.76 Allegan 37.7 33.8 1,421.29 1,142.44 1,274.26 Branch 38.2 28.2 1,459.24 795.24 1,077.24 Clinton 40.8 25.8 1,644.64 665.64 1,052.64 Lapeer 40.8 27.8 1,664.64 '772.84 1,134.24 Ionia 40.8 29.1 1,664.64 846.81 1,187.28 Lenawee 45.5 22.9 2,070.25 524.41 1,041.95 Cass 45.6 40.5 2,079.36 1,640.25 1,846.80 Livingston 50.5 36.1 2,550.25 1,303.21 1,823.05 Ottawa 52.0 35.4 2,704.00 1,253.16 1,840.80 Berrien 53.4 14.2 2,851.56 201.64 758.28 St. Clair 54.0 40.3 2,916.00 1,624.09 2,176.20 Monroe 54.4 38.6 2,959.36 1,489.96 2,099.84 Bay 54.9 28.5 3,014.01 812.25 1,564.65 Calhoun 55.5 39.4 3,080.25 1,552.36 2,186.70 Midland 56.1 53.1 3,147.21 2,819.61 2,978.91 Jackson 64.1 40.7 4,108.81 1,656.49 2,608.87 Saginaw 64.5 31.0 4,160.25 961.00 1,999.50 Ingham 72.7 32.6 5,285.29 1,062.76 2,370.02 Washtenaw 75.9 32.7 5,760.81 1,069.29 2,481.93 Kent 77.8 40.2 6,052.84 1,616.04 3,127.56 Kalamazoo 80.2 42.8 6,432.04 1,831.84 3,432.56 Genesee 81.9 51.9 6,707.61 2,693.61 4,250.61 Macomb 83.8 42.5 7,022.44 1,806.25 3,561.50 Musckegon 84.8 52.5 7,191.04 2,756.25 4,452.00 Oakland 90.6 56.0 8,208.36 3,136.00 5,073.60 Wayne 90.7 64.5 8,226.49 4,160.25 5,850.15 TBtals 1,947.6 1,319.7 115,702.98 50,443.33 73,709.36 a Source: See page 196. "T 1 : Per Cent Rural Non-Farm P0pu1ation (X) and Part-Time Farms -194- APPENDIX TABLE D-ll as a Percentage of all Farms (Y), by County, 1950a 2 2 County X Y X Y XY Sanilac 15.3 18.24 234.09 332.70 279.07 Huron 19.9 12.30 396.01 151.29 244.77 Montcalm 27.3 24.08 745.29 579.85 657.38 Van Buren 27.6 33.65 761.76 1,132.25 928.74 Hillsdale 31.5 24.86 992.25 618.02 783.09 Shiawassee 31.8 32.69 1,011.24 1,068.64 1,039.54 Isabella 32.7 20.19 1,069.29 407.64 660.21 Tuscola 32.8 22.55 1,075.84 508.50 739.64 Gratiot 33.0 17.83 1,089.00 317.91 588.39 Barry 35.2 33.51 1,239.04 1,122.92 1,179.55 Eaton 36.5 31.93 1,332.25 1,019.52 1,165.45 St. Joseph 36.8 30.33 1,354.24 919.91 1,116.14 Allegan 37.7 31.64 1,421.29 1,001.09 1,192.83 Branch 38.2 14.98 1,459.24 224.40 572.24 Clinton 40.8 26.39 1,664.64 696.43 1,076.71 Lapeer 40.8 27.72 1,664.64 768.40 1,130.98 Ionia 40.8 25.73 1,664.64 662.03 1,049.78 Lenaswee 45.5 25.03 2,070.25 626.50 1,138.87 Cass 45.6 35.43 2,079.36 1,255.28 1,615.61 Livingston 50.5 28.48 2,550.25 811.11 1,438.24 Ottawa 52.0 38.12 2,704.00 1,453.13 1,982.24 Berrien 53.4 35.86 2,851.56 1,285.94 1,914.92 St. Clair 54.0 35.14 2,916.00 1,234.82 1,897.56 Monroe 54.4 40.22 2,959.36 1,617.65 2,187.97 Bay 54.9 31.03 3,014.01 962.86 1,703.55 Calhoun 55.5 39.42 3,080.25 1,553.94 2,187.81 Midland 56.1 41.91 3,147.21 1,756.45 2,351.15 Jackson 64.1 39.38 4,108.81 1,550.78 2,524.26 Saginaw 64.5 31.27 4,160.25 977.81 2,016.92 Ingham 72.7 33.39 5,285.29 1,114.89 2,427.45 Washtenaw 75.9 32.14 5,760.81 1,032.98 2,439.43 Kent 77.8 36.91 6,052.84 1,362.35 2,871.60 Kalamazoo 80.2 43.25 6,432.04 1,870.56 3,468.65 Genessee 31.9 52.89 6,707.61 2,797.35 1,687.19 Macomb 83.3 37.92 7,022.44 1,437.93 3,158.74 Muckegon 84.8 42.59 7,191.04 1,813.91 3,611.63 Oakland 90.6 49.21 8,208.36 2,421.62 4,458.43 Wayne 90.7 54.99 8,226.49 3,023.90 4,987.59 Totals 1,947.6' 1,233.20 115,702.98 43,493.26 66,474.32 aSource: See page 196. -195- APPENDIX TABLE D—12 Per Cent Rural Non-Farm P0pu1ation (X) and Per Cent of Total Farmland Rented Out (Y), by County, 19503 County x Y x2 Y2 XY Sanilac 15.3 24.74 234.09 612.07 378.52 Huron 19.9 25.67 396.01 658.95 510.83 Montcalm 27.3 22.51 745.29 506.70 614.52 Van Buren 27.6 19.34 761.76 374.04 533.78 Hillsdale 31.5 31.82 992.25 1,012.51 1,002.23 Shiawassee 31.8 29.96 1,011.24 897.60 952.73 Isabella 32.7 31.41 1,069.29 986.59 1,027.11 Tuscola 32.8 28.47 1,075.84 810.54 933.82 Gratiot 33.0 37.81 1,089.00 1,429.60 1,247.30 Barry 25.2 21.28 1,239.04 486.11 749.06 Eaton 36.5 26.44 1,332.25 699.07 965.06 St. Joseph 36.8 30.33 1,354.24 919.91 1,116.14 Allegan 37.7 17.89 1,421.29 320.05 674.45 Branch 38.2 36.39 1,459.24 1,324.23 1,390.10 Clinton 40.8 29.35 1,664.64 861.42 1,197.48 Lapeer 40.8 25.60 1,664.64 655.36 1,044.48 Ionia 40.8 27.73 1,644,64 768.95 1,131.38 Lenaswee 45.5 37.55 2,070.25 1,410.00 1,708.53 Cass 45.6 30.02 2,079.36 901.20 1,368.91 Livingston 50.5 24.96 2,550.25 623.00 1,260.48 Ottawa 52.0 15.52 2,704.00 240.87 807.04 Berrien 53.4 18.31 2,851.56 335.26 977.75 St. Clair 54.0 19.98 2,916.00 399.20 1,078.92 Monroe 54.4 30.75 2,959.36 945.56 1,672.80 Bay 54.9 16.52 3,014.01 272.91 906.95 Calhoun 55.5 27.20 3,080.25 739.84 1,509.60 Midland 56.1 23.56 3,147.21 555.07 1,321.72 Jackson 64.1 23.10 4,108.81 533.61 1,480.71 Saginaw 64.5 20.43 4,160.25 417.38 1,317.34 Ingham 72.7 27.65 5,285.29 764.52 2,010.16 lashtenaw 75.9 28.20 5,760.81 795.24 2,140.38 Kent 77.8 20.50 6,052.84 420.25 1,594.90 Kalamazoo 80.2 26.65 6,432.04 710.22 2,137.33 Genessee 31.9 24.39 6,707.61 595.87 778.04 Macomb 83.3 22.67 7,022.44 513.93 1,888.41 Muckegon 84.8 15.03 7,191.04 255.90 1,274.54 Oakland 90.6 26.99 8,208.36 728.46 2,445,29 Wayne 90.7 35.22 8,226.49 1,240.45 3,194.45 Totals 1,947.6 981.94 115,702.98 26,712.44 48,343.24 aSource: See page 1960 -196- Source for all Appendix Tables D- 1 through D~12: 1950 United States Census of Agriculture: Michigan, United States Department of Commerce, Bureau of_the Census, United State Government Printing Office, Washington, D. C., Vol. I, part 6,1952; and 1950 United States Census of P0pu1ation: Michigan, United States Department of Commerce, Bureau of the Census, United States Government Printing Office, Wash- ington, D. C., Vol. II, part 22,1952. 1‘“ 8 Ame-TH- fs- ,‘ .3- -é,' ' 7" rib—seat,” :r"-—.‘ &_ a \i